FAQ

Quick answers plus deeper troubleshooting for real-world setups (local dev, VPS, multi-agent, OAuth/API keys, model failover). For runtime diagnostics, see Troubleshooting. For the full config reference, see Configuration.

First 60 seconds if something is broken

Quick status (first check)
```
pllan status
```
Fast local summary: OS + update, gateway/service reachability, agents/sessions, provider config + runtime issues (when gateway is reachable).
Pasteable report (safe to share)
```
pllan status --all
```
Read-only diagnosis with log tail (tokens redacted).
Daemon + port state
```
pllan gateway status
```
Shows supervisor runtime vs RPC reachability, the probe target URL, and which config the service likely used.
Deep probes
```
pllan status --deep
```
Runs gateway health checks + provider probes (requires a reachable gateway). See Health.
Tail the latest log
```
pllan logs --follow
```
If RPC is down, fall back to:
```
tail -f "$(ls -t /tmp/pllan/pllan-*.log | head -1)"
```
File logs are separate from service logs; see Logging and Troubleshooting.
Run the doctor (repairs)
```
pllan doctor
```
Repairs/migrates config/state + runs health checks. See Doctor.

Gateway snapshot

pllan health --json
pllan health --verbose   # shows the target URL + config path on errors

Asks the running gateway for a full snapshot (WS-only). See Health.

Quick start and first-run setup

I am stuck, fastest way to get unstuck

Use a local AI agent that can see your machine. That is far more effective than asking in Discord, because most “I’m stuck” cases are local config or environment issues that remote helpers cannot inspect.

Claude Code: https://www.anthropic.com/claude-code/
OpenAI Codex: https://openai.com/codex/

These tools can read the repo, run commands, inspect logs, and help fix your machine-level setup (PATH, services, permissions, auth files). Give them the full source checkout via the hackable (git) install:

curl -fsSL https://pllan.ai/install.sh | bash -s -- --install-method git

This installs Pllan from a git checkout, so the agent can read the code + docs and reason about the exact version you are running. You can always switch back to stable later by re-running the installer without --install-method git.Tip: ask the agent to plan and supervise the fix (step-by-step), then execute only the necessary commands. That keeps changes small and easier to audit.If you discover a real bug or fix, please file a GitHub issue or send a PR: https://github.com/pllan/pllan/issues https://github.com/pllan/pllan/pullsStart with these commands (share outputs when asking for help):

pllan status
pllan models status
pllan doctor

What they do:

pllan status: quick snapshot of gateway/agent health + basic config.
pllan models status: checks provider auth + model availability.
pllan doctor: validates and repairs common config/state issues.

Other useful CLI checks: pllan status --all, pllan logs --follow, pllan gateway status, pllan health --verbose.Quick debug loop: First 60 seconds if something is broken. Install docs: Install, Installer flags, Updating.

Recommended way to install and set up Pllan

The repo recommends running from source and using onboarding:

curl -fsSL https://pllan.ai/install.sh | bash
pllan onboard --install-daemon

The wizard can also build UI assets automatically. After onboarding, you typically run the Gateway on port 18789.From source (contributors/dev):

git clone https://github.com/pllan/pllan.git
cd pllan
pnpm install
pnpm build
pnpm ui:build # auto-installs UI deps on first run
pllan onboard

If you don’t have a global install yet, run it via pnpm pllan onboard.

How do I open the dashboard after onboarding?

The wizard opens your browser with a clean (non-tokenized) dashboard URL right after onboarding and also prints the link in the summary. Keep that tab open; if it didn’t launch, copy/paste the printed URL on the same machine.

How do I authenticate the dashboard (token) on localhost vs remote?

Localhost (same machine):

Open http://127.0.0.1:18789/.
If it asks for auth, paste the token from gateway.auth.token (or PLLAN_GATEWAY_TOKEN) into Control UI settings.
Retrieve it from the gateway host: pllan config get gateway.auth.token (or generate one: pllan doctor --generate-gateway-token).

Not on localhost:

Tailscale Serve (recommended): keep bind loopback, run pllan gateway --tailscale serve, open https://<magicdns>/. If gateway.auth.allowTailscale is true, identity headers satisfy Control UI/WebSocket auth (no token, assumes trusted gateway host); HTTP APIs still require token/password.
Tailnet bind: run pllan gateway --bind tailnet --token "<token>", open http://<tailscale-ip>:18789/, paste token in dashboard settings.
SSH tunnel: ssh -N -L 18789:127.0.0.1:18789 user@host then open http://127.0.0.1:18789/ and paste the token in Control UI settings.

See Dashboard and Web surfaces for bind modes and auth details.

What runtime do I need?

Node >= 22 is required. pnpm is recommended. Bun is not recommended for the Gateway.

Does it run on Raspberry Pi?

Yes. The Gateway is lightweight - docs list 512MB-1GB RAM, 1 core, and about 500MB disk as enough for personal use, and note that a Raspberry Pi 4 can run it.If you want extra headroom (logs, media, other services), 2GB is recommended, but it’s not a hard minimum.Tip: a small Pi/VPS can host the Gateway, and you can pair nodes on your laptop/phone for local screen/camera/canvas or command execution. See Nodes.

Any tips for Raspberry Pi installs?

Short version: it works, but expect rough edges.

Use a 64-bit OS and keep Node >= 22.
Prefer the hackable (git) install so you can see logs and update fast.
Start without channels/skills, then add them one by one.
If you hit weird binary issues, it is usually an ARM compatibility problem.

Docs: Linux, Install.

It is stuck on wake up my friend / onboarding will not hatch. What now?

That screen depends on the Gateway being reachable and authenticated. The TUI also sends “Wake up, my friend!” automatically on first hatch. If you see that line with no reply and tokens stay at 0, the agent never ran.

Restart the Gateway:

pllan gateway restart

Check status + auth:

pllan status
pllan models status
pllan logs --follow

If it still hangs, run:

pllan doctor

If the Gateway is remote, ensure the tunnel/Tailscale connection is up and that the UI is pointed at the right Gateway. See Remote access.

Can I migrate my setup to a new machine (Mac mini) without redoing onboarding?

Yes. Copy the state directory and workspace, then run Doctor once. This keeps your bot “exactly the same” (memory, session history, auth, and channel state) as long as you copy both locations:

Install Pllan on the new machine.
Copy $PLLAN_STATE_DIR (default: ~/.pllan) from the old machine.
Copy your workspace (default: ~/.pllan/workspace).
Run pllan doctor and restart the Gateway service.

That preserves config, auth profiles, WhatsApp creds, sessions, and memory. If you’re in remote mode, remember the gateway host owns the session store and workspace.Important: if you only commit/push your workspace to GitHub, you’re backing up memory + bootstrap files, but not session history or auth. Those live under ~/.pllan/ (for example ~/.pllan/agents/<agentId>/sessions/).Related: Migrating, Where things live on disk, Agent workspace, Doctor, Remote mode.

Where do I see what is new in the latest version?

Check the GitHub changelog: https://github.com/pllan/pllan/blob/main/CHANGELOG.mdNewest entries are at the top. If the top section is marked Unreleased, the next dated section is the latest shipped version. Entries are grouped by Highlights, Changes, and Fixes (plus docs/other sections when needed).

Cannot access docs.pllan.ai (SSL error)

Some Comcast/Xfinity connections incorrectly block docs.pllan.ai via Xfinity Advanced Security. Disable it or allowlist docs.pllan.ai, then retry. More detail: Troubleshooting. Please help us unblock it by reporting here: https://spa.xfinity.com/check_url_status.If you still can’t reach the site, the docs are mirrored on GitHub: https://github.com/pllan/pllan/tree/main/docs

Difference between stable and beta

Stable and beta are npm dist-tags, not separate code lines:

latest = stable
beta = early build for testing

We ship builds to beta, test them, and once a build is solid we promote that same version to latest. That’s why beta and stable can point at the same version.See what changed: https://github.com/pllan/pllan/blob/main/CHANGELOG.md

How do I install the beta version and what is the difference between beta and dev?

Beta is the npm dist-tag beta (may match latest). Dev is the moving head of main (git); when published, it uses the npm dist-tag dev.One-liners (macOS/Linux):

curl -fsSL --proto '=https' --tlsv1.2 https://pllan.ai/install.sh | bash -s -- --beta

curl -fsSL --proto '=https' --tlsv1.2 https://pllan.ai/install.sh | bash -s -- --install-method git

Windows installer (PowerShell): https://pllan.ai/install.ps1More detail: Development channels and Installer flags.

How do I try the latest bits?

Two options:

Dev channel (git checkout):

pllan update --channel dev

This switches to the main branch and updates from source.

Hackable install (from the installer site):

curl -fsSL https://pllan.ai/install.sh | bash -s -- --install-method git

That gives you a local repo you can edit, then update via git.If you prefer a clean clone manually, use:

git clone https://github.com/pllan/pllan.git
cd pllan
pnpm install
pnpm build

Docs: Update, Development channels, Install.

How long does install and onboarding usually take?

Rough guide:

Install: 2-5 minutes
Onboarding: 5-15 minutes depending on how many channels/models you configure

If it hangs, use Installer stuck and the fast debug loop in I am stuck.

Installer stuck? How do I get more feedback?

Re-run the installer with verbose output:

curl -fsSL https://pllan.ai/install.sh | bash -s -- --verbose

Beta install with verbose:

curl -fsSL https://pllan.ai/install.sh | bash -s -- --beta --verbose

For a hackable (git) install:

curl -fsSL https://pllan.ai/install.sh | bash -s -- --install-method git --verbose

Windows (PowerShell) equivalent:

# install.ps1 has no dedicated -Verbose flag yet.
Set-PSDebug -Trace 1
& ([scriptblock]::Create((iwr -useb https://pllan.ai/install.ps1))) -NoOnboard
Set-PSDebug -Trace 0

More options: Installer flags.

Windows install says git not found or pllan not recognized

Two common Windows issues:1) npm error spawn git / git not found

Install Git for Windows and make sure git is on your PATH.
Close and reopen PowerShell, then re-run the installer.

2) pllan is not recognized after install

Your npm global bin folder is not on PATH.
Check the path:
```
npm config get prefix
```
Add that directory to your user PATH (no \bin suffix needed on Windows; on most systems it is %AppData%\npm).
Close and reopen PowerShell after updating PATH.

If you want the smoothest Windows setup, use WSL2 instead of native Windows. Docs: Windows.

Windows exec output shows garbled Chinese text - what should I do?

This is usually a console code page mismatch on native Windows shells.Symptoms:

system.run/exec output renders Chinese as mojibake
The same command looks fine in another terminal profile

Quick workaround in PowerShell:

chcp 65001
[Console]::InputEncoding = [System.Text.UTF8Encoding]::new($false)
[Console]::OutputEncoding = [System.Text.UTF8Encoding]::new($false)
$OutputEncoding = [System.Text.UTF8Encoding]::new($false)

Then restart the Gateway and retry your command:

pllan gateway restart

If you still reproduce this on latest Pllan, track/report it in:

Issue #30640

The docs did not answer my question - how do I get a better answer?

Use the hackable (git) install so you have the full source and docs locally, then ask your bot (or Claude/Codex) from that folder so it can read the repo and answer precisely.

curl -fsSL https://pllan.ai/install.sh | bash -s -- --install-method git

More detail: Install and Installer flags.

How do I install Pllan on Linux?

Short answer: follow the Linux guide, then run onboarding.

Linux quick path + service install: Linux.
Full walkthrough: Getting Started.
Installer + updates: Install & updates.

How do I install Pllan on a VPS?

Any Linux VPS works. Install on the server, then use SSH/Tailscale to reach the Gateway.Guides: exe.dev, Hetzner, Fly.io. Remote access: Gateway remote.

Where are the cloud/VPS install guides?

We keep a hosting hub with the common providers. Pick one and follow the guide:

VPS hosting (all providers in one place)
Fly.io
Hetzner
exe.dev

How it works in the cloud: the Gateway runs on the server, and you access it from your laptop/phone via the Control UI (or Tailscale/SSH). Your state + workspace live on the server, so treat the host as the source of truth and back it up.You can pair nodes (Mac/iOS/Android/headless) to that cloud Gateway to access local screen/camera/canvas or run commands on your laptop while keeping the Gateway in the cloud.Hub: Platforms. Remote access: Gateway remote. Nodes: Nodes, Nodes CLI.

Can I ask Pllan to update itself?

Short answer: possible, not recommended. The update flow can restart the Gateway (which drops the active session), may need a clean git checkout, and can prompt for confirmation. Safer: run updates from a shell as the operator.Use the CLI:

pllan update
pllan update status
pllan update --channel stable|beta|dev
pllan update --tag <dist-tag|version>
pllan update --no-restart

If you must automate from an agent:

pllan update --yes --no-restart
pllan gateway restart

Docs: Update, Updating.

What does onboarding actually do?

pllan onboard is the recommended setup path. In local mode it walks you through:

Model/auth setup (provider OAuth/setup-token flows and API keys supported, plus local model options such as LM Studio)
Workspace location + bootstrap files
Gateway settings (bind/port/auth/tailscale)
Providers (WhatsApp, Telegram, Discord, Mattermost (plugin), Signal, iMessage)
Daemon install (LaunchAgent on macOS; systemd user unit on Linux/WSL2)
Health checks and skills selection

It also warns if your configured model is unknown or missing auth.

Do I need a Claude or OpenAI subscription to run this?

No. You can run Pllan with API keys (Anthropic/OpenAI/others) or with local-only models so your data stays on your device. Subscriptions (Claude Pro/Max or OpenAI Codex) are optional ways to authenticate those providers.If you choose Anthropic subscription auth, decide for yourself whether to use it: Anthropic has blocked some subscription usage outside Claude Code in the past. OpenAI Codex OAuth is explicitly supported for external tools like Pllan.Docs: Anthropic, OpenAI, Local models, Models.

Can I use Claude Max subscription without an API key?

Yes. You can authenticate with a setup-token instead of an API key. This is the subscription path.Claude Pro/Max subscriptions do not include an API key, so this is the technical path for subscription accounts. But this is your decision: Anthropic has blocked some subscription usage outside Claude Code in the past. If you want the clearest and safest supported path for production, use an Anthropic API key.

How does Anthropic setup-token auth work?

claude setup-token generates a token string via the Claude Code CLI (it is not available in the web console). You can run it on any machine. Choose Anthropic token (paste setup-token) in onboarding or paste it with pllan models auth paste-token --provider anthropic. The token is stored as an auth profile for the anthropic provider and used like an API key (no auto-refresh). More detail: OAuth.

Where do I find an Anthropic setup-token?

It is not in the Anthropic Console. The setup-token is generated by the Claude Code CLI on any machine:

claude setup-token

Copy the token it prints, then choose Anthropic token (paste setup-token) in onboarding. If you want to run it on the gateway host, use pllan models auth setup-token --provider anthropic. If you ran claude setup-token elsewhere, paste it on the gateway host with pllan models auth paste-token --provider anthropic. See Anthropic.

Do you support Claude subscription auth (Claude Pro or Max)?

Yes - via setup-token. Pllan no longer reuses Claude Code CLI OAuth tokens; use a setup-token or an Anthropic API key. Generate the token anywhere and paste it on the gateway host. See Anthropic and OAuth.Important: this is technical compatibility, not a policy guarantee. Anthropic has blocked some subscription usage outside Claude Code in the past. You need to decide whether to use it and verify Anthropic’s current terms. For production or multi-user workloads, Anthropic API key auth is the safer, recommended choice.

Why am I seeing HTTP 429 rate_limit_error from Anthropic?

That means your Anthropic quota/rate limit is exhausted for the current window. If you use a Claude subscription (setup-token), wait for the window to reset or upgrade your plan. If you use an Anthropic API key, check the Anthropic Console for usage/billing and raise limits as needed.If the message is specifically: Extra usage is required for long context requests, the request is trying to use Anthropic’s 1M context beta (context1m: true). That only works when your credential is eligible for long-context billing (API key billing or subscription with Extra Usage enabled).Tip: set a fallback model so Pllan can keep replying while a provider is rate-limited. See Models, OAuth, and /gateway/troubleshooting#anthropic-429-extra-usage-required-for-long-context.

Is AWS Bedrock supported?

Yes - via pi-ai’s Amazon Bedrock (Converse) provider with manual config. You must supply AWS credentials/region on the gateway host and add a Bedrock provider entry in your models config. See Amazon Bedrock and Model providers. If you prefer a managed key flow, an OpenAI-compatible proxy in front of Bedrock is still a valid option.

How does Codex auth work?

Pllan supports OpenAI Code (Codex) via OAuth (ChatGPT sign-in). Onboarding can run the OAuth flow and will set the default model to openai-codex/gpt-5.4 when appropriate. See Model providers and Onboarding (CLI).

Do you support OpenAI subscription auth (Codex OAuth)?

Yes. Pllan fully supports OpenAI Code (Codex) subscription OAuth. OpenAI explicitly allows subscription OAuth usage in external tools/workflows like Pllan. Onboarding can run the OAuth flow for you.See OAuth, Model providers, and Onboarding (CLI).

How do I set up Gemini CLI OAuth?

Gemini CLI uses a plugin auth flow, not a client id or secret in pllan.json.Steps:

Enable the plugin: pllan plugins enable google
Login: pllan models auth login --provider google-gemini-cli --set-default

This stores OAuth tokens in auth profiles on the gateway host. Details: Model providers.

Is a local model OK for casual chats?

Usually no. Pllan needs large context + strong safety; small cards truncate and leak. If you must, run the largest MiniMax M2.5 build you can locally (LM Studio) and see /gateway/local-models. Smaller/quantized models increase prompt-injection risk - see Security.

How do I keep hosted model traffic in a specific region?

Pick region-pinned endpoints. OpenRouter exposes US-hosted options for MiniMax, Kimi, and GLM; choose the US-hosted variant to keep data in-region. You can still list Anthropic/OpenAI alongside these by using models.mode: "merge" so fallbacks stay available while respecting the regioned provider you select.

Do I have to buy a Mac Mini to install this?

No. Pllan runs on macOS or Linux (Windows via WSL2). A Mac mini is optional - some people buy one as an always-on host, but a small VPS, home server, or Raspberry Pi-class box works too.You only need a Mac for macOS-only tools. For iMessage, use BlueBubbles (recommended) - the BlueBubbles server runs on any Mac, and the Gateway can run on Linux or elsewhere. If you want other macOS-only tools, run the Gateway on a Mac or pair a macOS node.Docs: BlueBubbles, Nodes, Mac remote mode.

Do I need a Mac mini for iMessage support?

You need some macOS device signed into Messages. It does not have to be a Mac mini - any Mac works. Use BlueBubbles (recommended) for iMessage - the BlueBubbles server runs on macOS, while the Gateway can run on Linux or elsewhere.Common setups:

Run the Gateway on Linux/VPS, and run the BlueBubbles server on any Mac signed into Messages.
Run everything on the Mac if you want the simplest single-machine setup.

Docs: BlueBubbles, Nodes, Mac remote mode.

If I buy a Mac mini to run Pllan, can I connect it to my MacBook Pro?

Yes. The Mac mini can run the Gateway, and your MacBook Pro can connect as a node (companion device). Nodes don’t run the Gateway - they provide extra capabilities like screen/camera/canvas and system.run on that device.Common pattern:

Gateway on the Mac mini (always-on).
MacBook Pro runs the macOS app or a node host and pairs to the Gateway.
Use pllan nodes status / pllan nodes list to see it.

Docs: Nodes, Nodes CLI.

Can I use Bun?

Bun is not recommended. We see runtime bugs, especially with WhatsApp and Telegram. Use Node for stable gateways.If you still want to experiment with Bun, do it on a non-production gateway without WhatsApp/Telegram.

Telegram: what goes in allowFrom?

channels.telegram.allowFrom is the human sender’s Telegram user ID (numeric). It is not the bot username.Onboarding accepts @username input and resolves it to a numeric ID, but Pllan authorization uses numeric IDs only.Safer (no third-party bot):

DM your bot, then run pllan logs --follow and read from.id.

Official Bot API:

DM your bot, then call https://api.telegram.org/bot<bot_token>/getUpdates and read message.from.id.

Third-party (less private):

DM @userinfobot or @getidsbot.

See /channels/telegram.

Can multiple people use one WhatsApp number with different Pllan instances?

Yes, via multi-agent routing. Bind each sender’s WhatsApp DM (peer kind: "direct", sender E.164 like +15551234567) to a different agentId, so each person gets their own workspace and session store. Replies still come from the same WhatsApp account, and DM access control (channels.whatsapp.dmPolicy / channels.whatsapp.allowFrom) is global per WhatsApp account. See Multi-Agent Routing and WhatsApp.

Can I run a "fast chat" agent and an "Opus for coding" agent?

Yes. Use multi-agent routing: give each agent its own default model, then bind inbound routes (provider account or specific peers) to each agent. Example config lives in Multi-Agent Routing. See also Models and Configuration.

Does Homebrew work on Linux?

Yes. Homebrew supports Linux (Linuxbrew). Quick setup:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
echo 'eval "$(/home/linuxbrew/.linuxbrew/bin/brew shellenv)"' >> ~/.profile
eval "$(/home/linuxbrew/.linuxbrew/bin/brew shellenv)"
brew install <formula>

If you run Pllan via systemd, ensure the service PATH includes /home/linuxbrew/.linuxbrew/bin (or your brew prefix) so brew-installed tools resolve in non-login shells. Recent builds also prepend common user bin dirs on Linux systemd services (for example ~/.local/bin, ~/.npm-global/bin, ~/.local/share/pnpm, ~/.bun/bin) and honor PNPM_HOME, NPM_CONFIG_PREFIX, BUN_INSTALL, VOLTA_HOME, ASDF_DATA_DIR, NVM_DIR, and FNM_DIR when set.

Difference between the hackable git install and npm install

Hackable (git) install: full source checkout, editable, best for contributors. You run builds locally and can patch code/docs.
npm install: global CLI install, no repo, best for “just run it.” Updates come from npm dist-tags.

Docs: Getting started, Updating.

Can I switch between npm and git installs later?

Yes. Install the other flavor, then run Doctor so the gateway service points at the new entrypoint. This does not delete your data - it only changes the Pllan code install. Your state (~/.pllan) and workspace (~/.pllan/workspace) stay untouched.From npm to git:

git clone https://github.com/pllan/pllan.git
cd pllan
pnpm install
pnpm build
pllan doctor
pllan gateway restart

From git to npm:

npm install -g pllan@latest
pllan doctor
pllan gateway restart

Doctor detects a gateway service entrypoint mismatch and offers to rewrite the service config to match the current install (use --repair in automation).Backup tips: see Backup strategy.

Should I run the Gateway on my laptop or a VPS?

Short answer: if you want 24/7 reliability, use a VPS. If you want the lowest friction and you’re okay with sleep/restarts, run it locally.Laptop (local Gateway)

Pros: no server cost, direct access to local files, live browser window.
Cons: sleep/network drops = disconnects, OS updates/reboots interrupt, must stay awake.

VPS / cloud

Pros: always-on, stable network, no laptop sleep issues, easier to keep running.
Cons: often run headless (use screenshots), remote file access only, you must SSH for updates.

Pllan-specific note: WhatsApp/Telegram/Slack/Mattermost (plugin)/Discord all work fine from a VPS. The only real trade-off is headless browser vs a visible window. See Browser.Recommended default: VPS if you had gateway disconnects before. Local is great when you’re actively using the Mac and want local file access or UI automation with a visible browser.

How important is it to run Pllan on a dedicated machine?

Not required, but recommended for reliability and isolation.

Dedicated host (VPS/Mac mini/Pi): always-on, fewer sleep/reboot interruptions, cleaner permissions, easier to keep running.
Shared laptop/desktop: totally fine for testing and active use, but expect pauses when the machine sleeps or updates.

If you want the best of both worlds, keep the Gateway on a dedicated host and pair your laptop as a node for local screen/camera/exec tools. See Nodes. For security guidance, read Security.

What are the minimum VPS requirements and recommended OS?

Pllan is lightweight. For a basic Gateway + one chat channel:

Absolute minimum: 1 vCPU, 1GB RAM, ~500MB disk.
Recommended: 1-2 vCPU, 2GB RAM or more for headroom (logs, media, multiple channels). Node tools and browser automation can be resource hungry.

OS: use Ubuntu LTS (or any modern Debian/Ubuntu). The Linux install path is best tested there.Docs: Linux, VPS hosting.

Can I run Pllan in a VM and what are the requirements?

Yes. Treat a VM the same as a VPS: it needs to be always on, reachable, and have enough RAM for the Gateway and any channels you enable.Baseline guidance:

Absolute minimum: 1 vCPU, 1GB RAM.
Recommended: 2GB RAM or more if you run multiple channels, browser automation, or media tools.
OS: Ubuntu LTS or another modern Debian/Ubuntu.

If you are on Windows, WSL2 is the easiest VM style setup and has the best tooling compatibility. See Windows, VPS hosting. If you are running macOS in a VM, see macOS VM.

What is Pllan?

What is Pllan, in one paragraph?

Pllan is a personal AI assistant you run on your own devices. It replies on the messaging surfaces you already use (WhatsApp, Telegram, Slack, Mattermost (plugin), Discord, Google Chat, Signal, iMessage, WebChat) and can also do voice + a live Canvas on supported platforms. The Gateway is the always-on control plane; the assistant is the product.

Value proposition

Pllan is not “just a Claude wrapper.” It’s a local-first control plane that lets you run a capable assistant on your own hardware, reachable from the chat apps you already use, with stateful sessions, memory, and tools - without handing control of your workflows to a hosted SaaS.Highlights:

Your devices, your data: run the Gateway wherever you want (Mac, Linux, VPS) and keep the workspace + session history local.
Real channels, not a web sandbox: WhatsApp/Telegram/Slack/Discord/Signal/iMessage/etc, plus mobile voice and Canvas on supported platforms.
Model-agnostic: use Anthropic, OpenAI, MiniMax, OpenRouter, etc., with per-agent routing and failover.
Local-only option: run local models so all data can stay on your device if you want.
Multi-agent routing: separate agents per channel, account, or task, each with its own workspace and defaults.
Open source and hackable: inspect, extend, and self-host without vendor lock-in.

Docs: Gateway, Channels, Multi-agent, Memory.

I just set it up - what should I do first?

Good first projects:

Build a website (WordPress, Shopify, or a simple static site).
Prototype a mobile app (outline, screens, API plan).
Organize files and folders (cleanup, naming, tagging).
Connect Gmail and automate summaries or follow ups.

It can handle large tasks, but it works best when you split them into phases and use sub agents for parallel work.

What are the top five everyday use cases for Pllan?

Everyday wins usually look like:

Personal briefings: summaries of inbox, calendar, and news you care about.
Research and drafting: quick research, summaries, and first drafts for emails or docs.
Reminders and follow ups: cron or heartbeat driven nudges and checklists.
Browser automation: filling forms, collecting data, and repeating web tasks.
Cross device coordination: send a task from your phone, let the Gateway run it on a server, and get the result back in chat.

Can Pllan help with lead gen, outreach, ads, and blogs for a SaaS?

Yes for research, qualification, and drafting. It can scan sites, build shortlists, summarize prospects, and write outreach or ad copy drafts.For outreach or ad runs, keep a human in the loop. Avoid spam, follow local laws and platform policies, and review anything before it is sent. The safest pattern is to let Pllan draft and you approve.Docs: Security.

What are the advantages vs Claude Code for web development?

Pllan is a personal assistant and coordination layer, not an IDE replacement. Use Claude Code or Codex for the fastest direct coding loop inside a repo. Use Pllan when you want durable memory, cross-device access, and tool orchestration.Advantages:

Persistent memory + workspace across sessions
Multi-platform access (WhatsApp, Telegram, TUI, WebChat)
Tool orchestration (browser, files, scheduling, hooks)
Always-on Gateway (run on a VPS, interact from anywhere)
Nodes for local browser/screen/camera/exec

Showcase: https://pllan.ai/showcase

Skills and automation

How do I customize skills without keeping the repo dirty?

Use managed overrides instead of editing the repo copy. Put your changes in ~/.pllan/skills/<name>/SKILL.md (or add a folder via skills.load.extraDirs in ~/.pllan/pllan.json). Precedence is <workspace>/skills > ~/.pllan/skills > bundled, so managed overrides win without touching git. Only upstream-worthy edits should live in the repo and go out as PRs.

Can I load skills from a custom folder?

Yes. Add extra directories via skills.load.extraDirs in ~/.pllan/pllan.json (lowest precedence). Default precedence remains: <workspace>/skills → ~/.pllan/skills → bundled → skills.load.extraDirs. clawhub installs into ./skills by default, which Pllan treats as <workspace>/skills on the next session.

How can I use different models for different tasks?

Today the supported patterns are:

Cron jobs: isolated jobs can set a model override per job.
Sub-agents: route tasks to separate agents with different default models.
On-demand switch: use /model to switch the current session model at any time.

See Cron jobs, Multi-Agent Routing, and Slash commands.

The bot freezes while doing heavy work. How do I offload that?

Use sub-agents for long or parallel tasks. Sub-agents run in their own session, return a summary, and keep your main chat responsive.Ask your bot to “spawn a sub-agent for this task” or use /subagents. Use /status in chat to see what the Gateway is doing right now (and whether it is busy).Token tip: long tasks and sub-agents both consume tokens. If cost is a concern, set a cheaper model for sub-agents via agents.defaults.subagents.model.Docs: Sub-agents.

How do thread-bound subagent sessions work on Discord?

Use thread bindings. You can bind a Discord thread to a subagent or session target so follow-up messages in that thread stay on that bound session.Basic flow:

Spawn with sessions_spawn using thread: true (and optionally mode: "session" for persistent follow-up).
Or manually bind with /focus <target>.
Use /agents to inspect binding state.
Use /session idle <duration|off> and /session max-age <duration|off> to control auto-unfocus.
Use /unfocus to detach the thread.

Required config:

Global defaults: session.threadBindings.enabled, session.threadBindings.idleHours, session.threadBindings.maxAgeHours.
Discord overrides: channels.discord.threadBindings.enabled, channels.discord.threadBindings.idleHours, channels.discord.threadBindings.maxAgeHours.
Auto-bind on spawn: set channels.discord.threadBindings.spawnSubagentSessions: true.

Docs: Sub-agents, Discord, Configuration Reference, Slash commands.

Cron or reminders do not fire. What should I check?

Cron runs inside the Gateway process. If the Gateway is not running continuously, scheduled jobs will not run.Checklist:

Confirm cron is enabled (cron.enabled) and PLLAN_SKIP_CRON is not set.
Check the Gateway is running 24/7 (no sleep/restarts).
Verify timezone settings for the job (--tz vs host timezone).

Debug:

pllan cron run <jobId> --force
pllan cron runs --id <jobId> --limit 50

Docs: Cron jobs, Cron vs Heartbeat.

How do I install skills on Linux?

Use ClawHub (CLI) or drop skills into your workspace. The macOS Skills UI isn’t available on Linux. Browse skills at https://clawhub.com.Install the ClawHub CLI (pick one package manager):

npm i -g clawhub

pnpm add -g clawhub

Can Pllan run tasks on a schedule or continuously in the background?

Yes. Use the Gateway scheduler:

Cron jobs for scheduled or recurring tasks (persist across restarts).
Heartbeat for “main session” periodic checks.
Isolated jobs for autonomous agents that post summaries or deliver to chats.

Docs: Cron jobs, Cron vs Heartbeat, Heartbeat.

Can I run Apple macOS-only skills from Linux?

Not directly. macOS skills are gated by metadata.pllan.os plus required binaries, and skills only appear in the system prompt when they are eligible on the Gateway host. On Linux, darwin-only skills (like apple-notes, apple-reminders, things-mac) will not load unless you override the gating.You have three supported patterns:Option A - run the Gateway on a Mac (simplest). Run the Gateway where the macOS binaries exist, then connect from Linux in remote mode or over Tailscale. The skills load normally because the Gateway host is macOS.Option B - use a macOS node (no SSH). Run the Gateway on Linux, pair a macOS node (menubar app), and set Node Run Commands to “Always Ask” or “Always Allow” on the Mac. Pllan can treat macOS-only skills as eligible when the required binaries exist on the node. The agent runs those skills via the nodes tool. If you choose “Always Ask”, approving “Always Allow” in the prompt adds that command to the allowlist.Option C - proxy macOS binaries over SSH (advanced). Keep the Gateway on Linux, but make the required CLI binaries resolve to SSH wrappers that run on a Mac. Then override the skill to allow Linux so it stays eligible.

Create an SSH wrapper for the binary (example: memo for Apple Notes):

#!/usr/bin/env bash
set -euo pipefail
exec ssh -T user@mac-host /opt/homebrew/bin/memo "$@"

Put the wrapper on PATH on the Linux host (for example ~/bin/memo).

Override the skill metadata (workspace or ~/.pllan/skills) to allow Linux:

---
name: apple-notes
description: Manage Apple Notes via the memo CLI on macOS.
metadata: { "pllan": { "os": ["darwin", "linux"], "requires": { "bins": ["memo"] } } }
---

Start a new session so the skills snapshot refreshes.

Do you have a Notion or HeyGen integration?

Not built-in today.Options:

Custom skill / plugin: best for reliable API access (Notion/HeyGen both have APIs).
Browser automation: works without code but is slower and more fragile.

If you want to keep context per client (agency workflows), a simple pattern is:

One Notion page per client (context + preferences + active work).
Ask the agent to fetch that page at the start of a session.

If you want a native integration, open a feature request or build a skill targeting those APIs.Install skills:

clawhub install <skill-slug>
clawhub update --all

ClawHub installs into ./skills under your current directory (or falls back to your configured Pllan workspace); Pllan treats that as <workspace>/skills on the next session. For shared skills across agents, place them in ~/.pllan/skills/<name>/SKILL.md. Some skills expect binaries installed via Homebrew; on Linux that means Linuxbrew (see the Homebrew Linux FAQ entry above). See Skills and ClawHub.

How do I use my existing signed-in Chrome with Pllan?

Use the built-in user browser profile, which attaches through Chrome DevTools MCP:

pllan browser --browser-profile user tabs
pllan browser --browser-profile user snapshot

If you want a custom name, create an explicit MCP profile:

pllan browser create-profile --name chrome-live --driver existing-session
pllan browser --browser-profile chrome-live tabs

This path is host-local. If the Gateway runs elsewhere, either run a node host on the browser machine or use remote CDP instead.

Sandboxing and memory

Is there a dedicated sandboxing doc?

Yes. See Sandboxing. For Docker-specific setup (full gateway in Docker or sandbox images), see Docker.

Docker feels limited - how do I enable full features?

The default image is security-first and runs as the node user, so it does not include system packages, Homebrew, or bundled browsers. For a fuller setup:

Persist /home/node with PLLAN_HOME_VOLUME so caches survive.
Bake system deps into the image with PLLAN_DOCKER_APT_PACKAGES.
Install Playwright browsers via the bundled CLI: node /app/node_modules/playwright-core/cli.js install chromium
Set PLAYWRIGHT_BROWSERS_PATH and ensure the path is persisted.

Docs: Docker, Browser.

Can I keep DMs personal but make groups public/sandboxed with one agent?

Yes - if your private traffic is DMs and your public traffic is groups.Use agents.defaults.sandbox.mode: "non-main" so group/channel sessions (non-main keys) run in Docker, while the main DM session stays on-host. Then restrict what tools are available in sandboxed sessions via tools.sandbox.tools.Setup walkthrough + example config: Groups: personal DMs + public groupsKey config reference: Gateway configuration

How do I bind a host folder into the sandbox?

Set agents.defaults.sandbox.docker.binds to ["host:path:mode"] (e.g., "/home/user/src:/src:ro"). Global + per-agent binds merge; per-agent binds are ignored when scope: "shared". Use :ro for anything sensitive and remember binds bypass the sandbox filesystem walls. See Sandboxing and Sandbox vs Tool Policy vs Elevated for examples and safety notes.

How does memory work?

Pllan memory is just Markdown files in the agent workspace:

Daily notes in memory/YYYY-MM-DD.md
Curated long-term notes in MEMORY.md (main/private sessions only)

Pllan also runs a silent pre-compaction memory flush to remind the model to write durable notes before auto-compaction. This only runs when the workspace is writable (read-only sandboxes skip it). See Memory.

Memory keeps forgetting things. How do I make it stick?

Ask the bot to write the fact to memory. Long-term notes belong in MEMORY.md, short-term context goes into memory/YYYY-MM-DD.md.This is still an area we are improving. It helps to remind the model to store memories; it will know what to do. If it keeps forgetting, verify the Gateway is using the same workspace on every run.Docs: Memory, Agent workspace.

Does memory persist forever? What are the limits?

Memory files live on disk and persist until you delete them. The limit is your storage, not the model. The session context is still limited by the model context window, so long conversations can compact or truncate. That is why memory search exists - it pulls only the relevant parts back into context.Docs: Memory, Context.

Does semantic memory search require an OpenAI API key?

Only if you use OpenAI embeddings. Codex OAuth covers chat/completions and does not grant embeddings access, so signing in with Codex (OAuth or the Codex CLI login) does not help for semantic memory search. OpenAI embeddings still need a real API key (OPENAI_API_KEY or models.providers.openai.apiKey).If you don’t set a provider explicitly, Pllan auto-selects a provider when it can resolve an API key (auth profiles, models.providers.*.apiKey, or env vars). It prefers OpenAI if an OpenAI key resolves, otherwise Gemini if a Gemini key resolves, then Voyage, then Mistral. If no remote key is available, memory search stays disabled until you configure it. If you have a local model path configured and present, Pllan prefers local. Ollama is supported when you explicitly set memorySearch.provider = "ollama".If you’d rather stay local, set memorySearch.provider = "local" (and optionally memorySearch.fallback = "none"). If you want Gemini embeddings, set memorySearch.provider = "gemini" and provide GEMINI_API_KEY (or memorySearch.remote.apiKey). We support OpenAI, Gemini, Voyage, Mistral, Ollama, or local embedding models - see Memory for the setup details.

Where things live on disk

Is all data used with Pllan saved locally?

No - Pllan’s state is local, but external services still see what you send them.

Local by default: sessions, memory files, config, and workspace live on the Gateway host (~/.pllan + your workspace directory).
Remote by necessity: messages you send to model providers (Anthropic/OpenAI/etc.) go to their APIs, and chat platforms (WhatsApp/Telegram/Slack/etc.) store message data on their servers.
You control the footprint: using local models keeps prompts on your machine, but channel traffic still goes through the channel’s servers.

Related: Agent workspace, Memory.

Where does Pllan store its data?

Everything lives under $PLLAN_STATE_DIR (default: ~/.pllan):

Path	Purpose
`$PLLAN_STATE_DIR/pllan.json`	Main config (JSON5)
`$PLLAN_STATE_DIR/credentials/oauth.json`	Legacy OAuth import (copied into auth profiles on first use)
`$PLLAN_STATE_DIR/agents/<agentId>/agent/auth-profiles.json`	Auth profiles (OAuth, API keys, and optional `keyRef`/`tokenRef`)
`$PLLAN_STATE_DIR/secrets.json`	Optional file-backed secret payload for `file` SecretRef providers
`$PLLAN_STATE_DIR/agents/<agentId>/agent/auth.json`	Legacy compatibility file (static `api_key` entries scrubbed)
`$PLLAN_STATE_DIR/credentials/`	Provider state (e.g. `whatsapp/<accountId>/creds.json`)
`$PLLAN_STATE_DIR/agents/`	Per-agent state (agentDir + sessions)
`$PLLAN_STATE_DIR/agents/<agentId>/sessions/`	Conversation history & state (per agent)
`$PLLAN_STATE_DIR/agents/<agentId>/sessions/sessions.json`	Session metadata (per agent)

Legacy single-agent path: ~/.pllan/agent/* (migrated by pllan doctor).Your workspace (AGENTS.md, memory files, skills, etc.) is separate and configured via agents.defaults.workspace (default: ~/.pllan/workspace).

Where should AGENTS.md / SOUL.md / USER.md / MEMORY.md live?

These files live in the agent workspace, not ~/.pllan.

Workspace (per agent): AGENTS.md, SOUL.md, IDENTITY.md, USER.md, MEMORY.md (or legacy fallback memory.md when MEMORY.md is absent), memory/YYYY-MM-DD.md, optional HEARTBEAT.md.
State dir (~/.pllan): config, credentials, auth profiles, sessions, logs, and shared skills (~/.pllan/skills).

Default workspace is ~/.pllan/workspace, configurable via:

{
  agents: { defaults: { workspace: "~/.pllan/workspace" } },
}

If the bot “forgets” after a restart, confirm the Gateway is using the same workspace on every launch (and remember: remote mode uses the gateway host’s workspace, not your local laptop).Tip: if you want a durable behavior or preference, ask the bot to write it into AGENTS.md or MEMORY.md rather than relying on chat history.See Agent workspace and Memory.

Recommended backup strategy

Put your agent workspace in a private git repo and back it up somewhere private (for example GitHub private). This captures memory + AGENTS/SOUL/USER files, and lets you restore the assistant’s “mind” later.Do not commit anything under ~/.pllan (credentials, sessions, tokens, or encrypted secrets payloads). If you need a full restore, back up both the workspace and the state directory separately (see the migration question above).Docs: Agent workspace.

How do I completely uninstall Pllan?

See the dedicated guide: Uninstall.

Can agents work outside the workspace?

Yes. The workspace is the default cwd and memory anchor, not a hard sandbox. Relative paths resolve inside the workspace, but absolute paths can access other host locations unless sandboxing is enabled. If you need isolation, use agents.defaults.sandbox or per-agent sandbox settings. If you want a repo to be the default working directory, point that agent’s workspace to the repo root. The Pllan repo is just source code; keep the workspace separate unless you intentionally want the agent to work inside it.Example (repo as default cwd):

{
  agents: {
    defaults: {
      workspace: "~/Projects/my-repo",
    },
  },
}

I'm in remote mode - where is the session store?

Session state is owned by the gateway host. If you’re in remote mode, the session store you care about is on the remote machine, not your local laptop. See Session management.

Config basics

What format is the config? Where is it?

Pllan reads an optional JSON5 config from $PLLAN_CONFIG_PATH (default: ~/.pllan/pllan.json):

$PLLAN_CONFIG_PATH

If the file is missing, it uses safe-ish defaults (including a default workspace of ~/.pllan/workspace).

I set gateway.bind: "lan" (or "tailnet") and now nothing listens / the UI says unauthorized

Non-loopback binds require auth. Configure gateway.auth.mode + gateway.auth.token (or use PLLAN_GATEWAY_TOKEN).

{
  gateway: {
    bind: "lan",
    auth: {
      mode: "token",
      token: "replace-me",
    },
  },
}

Notes:

gateway.remote.token / .password do not enable local gateway auth by themselves.
Local call paths can use gateway.remote.* as fallback only when gateway.auth.* is unset.
If gateway.auth.token / gateway.auth.password is explicitly configured via SecretRef and unresolved, resolution fails closed (no remote fallback masking).
The Control UI authenticates via connect.params.auth.token (stored in app/UI settings). Avoid putting tokens in URLs.

Why do I need a token on localhost now?

Pllan enforces token auth by default, including loopback. If no token is configured, gateway startup auto-generates one and saves it to gateway.auth.token, so local WS clients must authenticate. This blocks other local processes from calling the Gateway.If you really want open loopback, set gateway.auth.mode: "none" explicitly in your config. Doctor can generate a token for you any time: pllan doctor --generate-gateway-token.

Do I have to restart after changing config?

The Gateway watches the config and supports hot-reload:

gateway.reload.mode: "hybrid" (default): hot-apply safe changes, restart for critical ones
hot, restart, off are also supported

How do I disable funny CLI taglines?

Set cli.banner.taglineMode in config:

{
  cli: {
    banner: {
      taglineMode: "off", // random | default | off
    },
  },
}

off: hides tagline text but keeps the banner title/version line.
default: uses All your chats, one Pllan. every time.
random: rotating funny/seasonal taglines (default behavior).
If you want no banner at all, set env PLLAN_HIDE_BANNER=1.

How do I enable web search (and web fetch)?

web_fetch works without an API key. web_search requires a key for your selected provider (Brave, Gemini, Grok, Kimi, or Perplexity). Recommended: run pllan configure --section web and choose a provider. Environment alternatives:

Brave: BRAVE_API_KEY
Gemini: GEMINI_API_KEY
Grok: XAI_API_KEY
Kimi: KIMI_API_KEY or MOONSHOT_API_KEY
Perplexity: PERPLEXITY_API_KEY or OPENROUTER_API_KEY

{
  plugins: {
    entries: {
      brave: {
        config: {
          webSearch: {
            apiKey: "BRAVE_API_KEY_HERE",
          },
        },
      },
    },
  },
  tools: {
    web: {
      search: {
        enabled: true,
        provider: "brave",
        maxResults: 5,
      },
      fetch: {
        enabled: true,
      },
    },
  },
}

Provider-specific web-search config now lives under plugins.entries.<plugin>.config.webSearch.*. Legacy tools.web.search.* provider paths still load temporarily for compatibility, but they should not be used for new configs.Notes:

If you use allowlists, add web_search/web_fetch or group:web.
web_fetch is enabled by default (unless explicitly disabled).
Daemons read env vars from ~/.pllan/.env (or the service environment).

Docs: Web tools.

config.apply wiped my config. How do I recover and avoid this?

config.apply replaces the entire config. If you send a partial object, everything else is removed.Recover:

Restore from backup (git or a copied ~/.pllan/pllan.json).
If you have no backup, re-run pllan doctor and reconfigure channels/models.
If this was unexpected, file a bug and include your last known config or any backup.
A local coding agent can often reconstruct a working config from logs or history.

Avoid it:

Use pllan config set for small changes.
Use pllan configure for interactive edits.

Docs: Config, Configure, Doctor.

How do I run a central Gateway with specialized workers across devices?

The common pattern is one Gateway (e.g. Raspberry Pi) plus nodes and agents:

Gateway (central): owns channels (Signal/WhatsApp), routing, and sessions.
Nodes (devices): Macs/iOS/Android connect as peripherals and expose local tools (system.run, canvas, camera).
Agents (workers): separate brains/workspaces for special roles (e.g. “Hetzner ops”, “Personal data”).
Sub-agents: spawn background work from a main agent when you want parallelism.
TUI: connect to the Gateway and switch agents/sessions.

Docs: Nodes, Remote access, Multi-Agent Routing, Sub-agents, TUI.

Can the Pllan browser run headless?

Yes. It’s a config option:

{
  browser: { headless: true },
  agents: {
    defaults: {
      sandbox: { browser: { headless: true } },
    },
  },
}

Default is false (headful). Headless is more likely to trigger anti-bot checks on some sites. See Browser.Headless uses the same Chromium engine and works for most automation (forms, clicks, scraping, logins). The main differences:

No visible browser window (use screenshots if you need visuals).
Some sites are stricter about automation in headless mode (CAPTCHAs, anti-bot). For example, X/Twitter often blocks headless sessions.

How do I use Brave for browser control?

Set browser.executablePath to your Brave binary (or any Chromium-based browser) and restart the Gateway. See the full config examples in Browser.

Remote gateways and nodes

How do commands propagate between Telegram, the gateway, and nodes?

Telegram messages are handled by the gateway. The gateway runs the agent and only then calls nodes over the Gateway WebSocket when a node tool is needed:Telegram → Gateway → Agent → node.* → Node → Gateway → TelegramNodes don’t see inbound provider traffic; they only receive node RPC calls.

How can my agent access my computer if the Gateway is hosted remotely?

Short answer: pair your computer as a node. The Gateway runs elsewhere, but it can call node.* tools (screen, camera, system) on your local machine over the Gateway WebSocket.Typical setup:

Run the Gateway on the always-on host (VPS/home server).
Put the Gateway host + your computer on the same tailnet.
Ensure the Gateway WS is reachable (tailnet bind or SSH tunnel).
Open the macOS app locally and connect in Remote over SSH mode (or direct tailnet) so it can register as a node.

Approve the node on the Gateway:

pllan devices list
pllan devices approve <requestId>

No separate TCP bridge is required; nodes connect over the Gateway WebSocket.Security reminder: pairing a macOS node allows system.run on that machine. Only pair devices you trust, and review Security.Docs: Nodes, Gateway protocol, macOS remote mode, Security.

Tailscale is connected but I get no replies. What now?

Check the basics:

Gateway is running: pllan gateway status
Gateway health: pllan status
Channel health: pllan channels status

Then verify auth and routing:

If you use Tailscale Serve, make sure gateway.auth.allowTailscale is set correctly.
If you connect via SSH tunnel, confirm the local tunnel is up and points at the right port.
Confirm your allowlists (DM or group) include your account.

Docs: Tailscale, Remote access, Channels.

Can two Pllan instances talk to each other (local + VPS)?

Yes. There is no built-in “bot-to-bot” bridge, but you can wire it up in a few reliable ways:Simplest: use a normal chat channel both bots can access (Telegram/Slack/WhatsApp). Have Bot A send a message to Bot B, then let Bot B reply as usual.CLI bridge (generic): run a script that calls the other Gateway with pllan agent --message ... --deliver, targeting a chat where the other bot listens. If one bot is on a remote VPS, point your CLI at that remote Gateway via SSH/Tailscale (see Remote access).Example pattern (run from a machine that can reach the target Gateway):

pllan agent --message "Hello from local bot" --deliver --channel telegram --reply-to <chat-id>

Tip: add a guardrail so the two bots do not loop endlessly (mention-only, channel allowlists, or a “do not reply to bot messages” rule).Docs: Remote access, Agent CLI, Agent send.

Do I need separate VPSes for multiple agents?

No. One Gateway can host multiple agents, each with its own workspace, model defaults, and routing. That is the normal setup and it is much cheaper and simpler than running one VPS per agent.Use separate VPSes only when you need hard isolation (security boundaries) or very different configs that you do not want to share. Otherwise, keep one Gateway and use multiple agents or sub-agents.

Is there a benefit to using a node on my personal laptop instead of SSH from a VPS?

Yes - nodes are the first-class way to reach your laptop from a remote Gateway, and they unlock more than shell access. The Gateway runs on macOS/Linux (Windows via WSL2) and is lightweight (a small VPS or Raspberry Pi-class box is fine; 4 GB RAM is plenty), so a common setup is an always-on host plus your laptop as a node.

No inbound SSH required. Nodes connect out to the Gateway WebSocket and use device pairing.
Safer execution controls. system.run is gated by node allowlists/approvals on that laptop.
More device tools. Nodes expose canvas, camera, and screen in addition to system.run.
Local browser automation. Keep the Gateway on a VPS, but run Chrome locally through a node host on the laptop, or attach to local Chrome on the host via Chrome MCP.

SSH is fine for ad-hoc shell access, but nodes are simpler for ongoing agent workflows and device automation.Docs: Nodes, Nodes CLI, Browser.

Do nodes run a gateway service?

No. Only one gateway should run per host unless you intentionally run isolated profiles (see Multiple gateways). Nodes are peripherals that connect to the gateway (iOS/Android nodes, or macOS “node mode” in the menubar app). For headless node hosts and CLI control, see Node host CLI.A full restart is required for gateway, discovery, and canvasHost changes.

Is there an API / RPC way to apply config?

Yes. config.apply validates + writes the full config and restarts the Gateway as part of the operation.

Minimal sane config for a first install

{
  agents: { defaults: { workspace: "~/.pllan/workspace" } },
  channels: { whatsapp: { allowFrom: ["+15555550123"] } },
}

This sets your workspace and restricts who can trigger the bot.

How do I set up Tailscale on a VPS and connect from my Mac?

Minimal steps:

Install + login on the VPS

curl -fsSL https://tailscale.com/install.sh | sh
sudo tailscale up

Install + login on your Mac
- Use the Tailscale app and sign in to the same tailnet.
Enable MagicDNS (recommended)
- In the Tailscale admin console, enable MagicDNS so the VPS has a stable name.
Use the tailnet hostname
- SSH: ssh user@your-vps.tailnet-xxxx.ts.net
- Gateway WS: ws://your-vps.tailnet-xxxx.ts.net:18789

If you want the Control UI without SSH, use Tailscale Serve on the VPS:

pllan gateway --tailscale serve

This keeps the gateway bound to loopback and exposes HTTPS via Tailscale. See Tailscale.

How do I connect a Mac node to a remote Gateway (Tailscale Serve)?

Serve exposes the Gateway Control UI + WS. Nodes connect over the same Gateway WS endpoint.Recommended setup:

Make sure the VPS + Mac are on the same tailnet.
Use the macOS app in Remote mode (SSH target can be the tailnet hostname). The app will tunnel the Gateway port and connect as a node.

Approve the node on the gateway:

pllan devices list
pllan devices approve <requestId>

Docs: Gateway protocol, Discovery, macOS remote mode.

Should I install on a second laptop or just add a node?

If you only need local tools (screen/camera/exec) on the second laptop, add it as a node. That keeps a single Gateway and avoids duplicated config. Local node tools are currently macOS-only, but we plan to extend them to other OSes.Install a second Gateway only when you need hard isolation or two fully separate bots.Docs: Nodes, Nodes CLI, Multiple gateways.

Env vars and .env loading

How does Pllan load environment variables?

Pllan reads env vars from the parent process (shell, launchd/systemd, CI, etc.) and additionally loads:

.env from the current working directory
a global fallback .env from ~/.pllan/.env (aka $PLLAN_STATE_DIR/.env)

Neither .env file overrides existing env vars.You can also define inline env vars in config (applied only if missing from the process env):

{
  env: {
    OPENROUTER_API_KEY: "sk-or-...",
    vars: { GROQ_API_KEY: "gsk-..." },
  },
}

See /environment for full precedence and sources.

I started the Gateway via the service and my env vars disappeared. What now?

Two common fixes:

Put the missing keys in ~/.pllan/.env so they’re picked up even when the service doesn’t inherit your shell env.
Enable shell import (opt-in convenience):

{
  env: {
    shellEnv: {
      enabled: true,
      timeoutMs: 15000,
    },
  },
}

This runs your login shell and imports only missing expected keys (never overrides). Env var equivalents: PLLAN_LOAD_SHELL_ENV=1, PLLAN_SHELL_ENV_TIMEOUT_MS=15000.

I set COPILOT_GITHUB_TOKEN, but models status shows "Shell env: off." Why?

pllan models status reports whether shell env import is enabled. “Shell env: off” does not mean your env vars are missing - it just means Pllan won’t load your login shell automatically.If the Gateway runs as a service (launchd/systemd), it won’t inherit your shell environment. Fix by doing one of these:

Put the token in ~/.pllan/.env:
```
COPILOT_GITHUB_TOKEN=...
```
Or enable shell import (env.shellEnv.enabled: true).
Or add it to your config env block (applies only if missing).

Then restart the gateway and recheck:

pllan models status

Copilot tokens are read from COPILOT_GITHUB_TOKEN (also GH_TOKEN / GITHUB_TOKEN). See /concepts/model-providers and /environment.

Sessions and multiple chats

How do I start a fresh conversation?

Send /new or /reset as a standalone message. See Session management.

Do sessions reset automatically if I never send /new?

Yes. Sessions expire after session.idleMinutes (default 60). The next message starts a fresh session id for that chat key. This does not delete transcripts - it just starts a new session.

{
  session: {
    idleMinutes: 240,
  },
}

Is there a way to make a team of Pllan instances (one CEO and many agents)?

Yes, via multi-agent routing and sub-agents. You can create one coordinator agent and several worker agents with their own workspaces and models.That said, this is best seen as a fun experiment. It is token heavy and often less efficient than using one bot with separate sessions. The typical model we envision is one bot you talk to, with different sessions for parallel work. That bot can also spawn sub-agents when needed.Docs: Multi-agent routing, Sub-agents, Agents CLI.

Why did context get truncated mid-task? How do I prevent it?

Session context is limited by the model window. Long chats, large tool outputs, or many files can trigger compaction or truncation.What helps:

Ask the bot to summarize the current state and write it to a file.
Use /compact before long tasks, and /new when switching topics.
Keep important context in the workspace and ask the bot to read it back.
Use sub-agents for long or parallel work so the main chat stays smaller.
Pick a model with a larger context window if this happens often.

How do I completely reset Pllan but keep it installed?

Use the reset command:

pllan reset

Non-interactive full reset:

pllan reset --scope full --yes --non-interactive

Then re-run setup:

pllan onboard --install-daemon

Notes:

Onboarding also offers Reset if it sees an existing config. See Onboarding (CLI).
If you used profiles (--profile / PLLAN_PROFILE), reset each state dir (defaults are ~/.pllan-<profile>).
Dev reset: pllan gateway --dev --reset (dev-only; wipes dev config + credentials + sessions + workspace).

I am getting "context too large" errors - how do I reset or compact?

Use one of these:

Compact (keeps the conversation but summarizes older turns):
```
/compact
```
or /compact <instructions> to guide the summary.
Reset (fresh session ID for the same chat key):
```
/new
/reset
```

If it keeps happening:

Enable or tune session pruning (agents.defaults.contextPruning) to trim old tool output.
Use a model with a larger context window.

Docs: Compaction, Session pruning, Session management.

Why am I seeing "LLM request rejected: messages.content.tool_use.input field required"?

This is a provider validation error: the model emitted a tool_use block without the required input. It usually means the session history is stale or corrupted (often after long threads or a tool/schema change).Fix: start a fresh session with /new (standalone message).

Why am I getting heartbeat messages every 30 minutes?

Heartbeats run every 30m by default. Tune or disable them:

{
  agents: {
    defaults: {
      heartbeat: {
        every: "2h", // or "0m" to disable
      },
    },
  },
}

If HEARTBEAT.md exists but is effectively empty (only blank lines and markdown headers like # Heading), Pllan skips the heartbeat run to save API calls. If the file is missing, the heartbeat still runs and the model decides what to do.Per-agent overrides use agents.list[].heartbeat. Docs: Heartbeat.

Do I need to add a "bot account" to a WhatsApp group?

No. Pllan runs on your own account, so if you’re in the group, Pllan can see it. By default, group replies are blocked until you allow senders (groupPolicy: "allowlist").If you want only you to be able to trigger group replies:

{
  channels: {
    whatsapp: {
      groupPolicy: "allowlist",
      groupAllowFrom: ["+15551234567"],
    },
  },
}

How do I get the JID of a WhatsApp group?

Option 1 (fastest): tail logs and send a test message in the group:

pllan logs --follow --json

Look for chatId (or from) ending in @g.us, like: 1234567890-1234567890@g.us.Option 2 (if already configured/allowlisted): list groups from config:

pllan directory groups list --channel whatsapp

Docs: WhatsApp, Directory, Logs.

Why does Pllan not reply in a group?

Two common causes:

Mention gating is on (default). You must @mention the bot (or match mentionPatterns).
You configured channels.whatsapp.groups without "*" and the group isn’t allowlisted.

See Groups and Group messages.

Do groups/threads share context with DMs?

How many workspaces and agents can I create?

No hard limits. Dozens (even hundreds) are fine, but watch for:

Disk growth: sessions + transcripts live under ~/.pllan/agents/<agentId>/sessions/.
Token cost: more agents means more concurrent model usage.
Ops overhead: per-agent auth profiles, workspaces, and channel routing.

Tips:

Keep one active workspace per agent (agents.defaults.workspace).
Prune old sessions (delete JSONL or store entries) if disk grows.
Use pllan doctor to spot stray workspaces and profile mismatches.

Can I run multiple bots or chats at the same time (Slack), and how should I set that up?

Yes. Use Multi-Agent Routing to run multiple isolated agents and route inbound messages by channel/account/peer. Slack is supported as a channel and can be bound to specific agents.Browser access is powerful but not “do anything a human can” - anti-bot, CAPTCHAs, and MFA can still block automation. For the most reliable browser control, use local Chrome MCP on the host, or use CDP on the machine that actually runs the browser.Best-practice setup:

Always-on Gateway host (VPS/Mac mini).
One agent per role (bindings).
Slack channel(s) bound to those agents.
Local browser via Chrome MCP or a node when needed.

Docs: Multi-Agent Routing, Slack, Browser, Nodes.

Models: defaults, selection, aliases, switching

What is the "default model"?

Pllan’s default model is whatever you set as:

agents.defaults.model.primary

Models are referenced as provider/model (example: anthropic/claude-opus-4-6). If you omit the provider, Pllan currently assumes anthropic as a temporary deprecation fallback - but you should still explicitly set provider/model.

What model do you recommend?

How do I switch models without wiping my config?

Use model commands or edit only the model fields. Avoid full config replaces.Safe options:

/model in chat (quick, per-session)
pllan models set ... (updates just model config)
pllan configure --section model (interactive)
edit agents.defaults.model in ~/.pllan/pllan.json

Avoid config.apply with a partial object unless you intend to replace the whole config. If you did overwrite config, restore from backup or re-run pllan doctor to repair.Docs: Models, Configure, Config, Doctor.

Can I use self-hosted models (llama.cpp, vLLM, Ollama)?

Yes. Ollama is the easiest path for local models.Quickest setup:

Install Ollama from https://ollama.com/download
Pull a local model such as ollama pull glm-4.7-flash
If you want Ollama Cloud too, run ollama signin
Run pllan onboard and choose Ollama
Pick Local or Cloud + Local

Notes:

Cloud + Local gives you Ollama Cloud models plus your local Ollama models
cloud models such as kimi-k2.5:cloud do not need a local pull
for manual switching, use pllan models list and pllan models set ollama/<model>

Security note: smaller or heavily quantized models are more vulnerable to prompt injection. We strongly recommend large models for any bot that can use tools. If you still want small models, enable sandboxing and strict tool allowlists.Docs: Ollama, Local models, Model providers, Security, Sandboxing.

What do Pllan, Flawd, and Krill use for models?

These deployments can differ and may change over time; there is no fixed provider recommendation.
Check the current runtime setting on each gateway with pllan models status.
For security-sensitive/tool-enabled agents, use the strongest latest-generation model available.

How do I switch models on the fly (without restarting)?

Use the /model command as a standalone message:

/model sonnet
/model haiku
/model opus
/model gpt
/model gpt-mini
/model gemini
/model gemini-flash

You can list available models with /model, /model list, or /model status./model (and /model list) shows a compact, numbered picker. Select by number:

/model 3

You can also force a specific auth profile for the provider (per session):

/model opus@anthropic:default
/model opus@anthropic:work

Tip: /model status shows which agent is active, which auth-profiles.json file is being used, and which auth profile will be tried next. It also shows the configured provider endpoint (baseUrl) and API mode (api) when available.How do I unpin a profile I set with @profile?Re-run /model without the @profile suffix:

/model anthropic/claude-opus-4-6

If you want to return to the default, pick it from /model (or send /model <default provider/model>). Use /model status to confirm which auth profile is active.

Can I use GPT 5.2 for daily tasks and Codex 5.3 for coding?

Yes. Set one as default and switch as needed:

Quick switch (per session): /model gpt-5.2 for daily tasks, /model openai-codex/gpt-5.4 for coding with Codex OAuth.
Default + switch: set agents.defaults.model.primary to openai/gpt-5.2, then switch to openai-codex/gpt-5.4 when coding (or the other way around).
Sub-agents: route coding tasks to sub-agents with a different default model.

See Models and Slash commands.

Why do I see "Model ... is not allowed" and then no reply?

If agents.defaults.models is set, it becomes the allowlist for /model and any session overrides. Choosing a model that isn’t in that list returns:

Model "provider/model" is not allowed. Use /model to list available models.

That error is returned instead of a normal reply. Fix: add the model to agents.defaults.models, remove the allowlist, or pick a model from /model list.

Why do I see "Unknown model: minimax/MiniMax-M2.7"?

This means the provider isn’t configured (no MiniMax provider config or auth profile was found), so the model can’t be resolved. A fix for this detection is in 2026.1.12 (unreleased at the time of writing).Fix checklist:

Upgrade to 2026.1.12 (or run from source main), then restart the gateway.
Make sure MiniMax is configured (wizard or JSON), or that a MiniMax API key exists in env/auth profiles so the provider can be injected.
Use the exact model id (case-sensitive): minimax/MiniMax-M2.7, minimax/MiniMax-M2.7-highspeed, minimax/MiniMax-M2.5, or minimax/MiniMax-M2.5-highspeed.
Run:
```
pllan models list
```
and pick from the list (or /model list in chat).

See MiniMax and Models.

Can I use MiniMax as my default and OpenAI for complex tasks?

Yes. Use MiniMax as the default and switch models per session when needed. Fallbacks are for errors, not “hard tasks,” so use /model or a separate agent.Option A: switch per session

{
  env: { MINIMAX_API_KEY: "sk-...", OPENAI_API_KEY: "sk-..." },
  agents: {
    defaults: {
      model: { primary: "minimax/MiniMax-M2.7" },
      models: {
        "minimax/MiniMax-M2.7": { alias: "minimax" },
        "openai/gpt-5.2": { alias: "gpt" },
      },
    },
  },
}

Then:

/model gpt

Option B: separate agents

Agent A default: MiniMax
Agent B default: OpenAI
Route by agent or use /agent to switch

Docs: Models, Multi-Agent Routing, MiniMax, OpenAI.

Are opus / sonnet / gpt built-in shortcuts?

Yes. Pllan ships a few default shorthands (only applied when the model exists in agents.defaults.models):

opus → anthropic/claude-opus-4-6
sonnet → anthropic/claude-sonnet-4-6
gpt → openai/gpt-5.4
gpt-mini → openai/gpt-5-mini
gemini → google/gemini-3.1-pro-preview
gemini-flash → google/gemini-3-flash-preview
gemini-flash-lite → google/gemini-3.1-flash-lite-preview

If you set your own alias with the same name, your value wins.

How do I define/override model shortcuts (aliases)?

Aliases come from agents.defaults.models.<modelId>.alias. Example:

{
  agents: {
    defaults: {
      model: { primary: "anthropic/claude-opus-4-6" },
      models: {
        "anthropic/claude-opus-4-6": { alias: "opus" },
        "anthropic/claude-sonnet-4-6": { alias: "sonnet" },
        "anthropic/claude-haiku-4-5": { alias: "haiku" },
      },
    },
  },
}

Then /model sonnet (or /<alias> when supported) resolves to that model ID.

How do I add models from other providers like OpenRouter or Z.AI?

OpenRouter (pay-per-token; many models):

{
  agents: {
    defaults: {
      model: { primary: "openrouter/anthropic/claude-sonnet-4-6" },
      models: { "openrouter/anthropic/claude-sonnet-4-6": {} },
    },
  },
  env: { OPENROUTER_API_KEY: "sk-or-..." },
}

Z.AI (GLM models):

{
  agents: {
    defaults: {
      model: { primary: "zai/glm-5" },
      models: { "zai/glm-5": {} },
    },
  },
  env: { ZAI_API_KEY: "..." },
}

If you reference a provider/model but the required provider key is missing, you’ll get a runtime auth error (e.g. No API key found for provider "zai").No API key found for provider after adding a new agentThis usually means the new agent has an empty auth store. Auth is per-agent and stored in:

~/.pllan/agents/<agentId>/agent/auth-profiles.json

Fix options:

Run pllan agents add <id> and configure auth during the wizard.
Or copy auth-profiles.json from the main agent’s agentDir into the new agent’s agentDir.

Do not reuse agentDir across agents; it causes auth/session collisions.

Model failover and “All models failed”

How does failover work?

Failover happens in two stages:

Auth profile rotation within the same provider.
Model fallback to the next model in agents.defaults.model.fallbacks.

Cooldowns apply to failing profiles (exponential backoff), so Pllan can keep responding even when a provider is rate-limited or temporarily failing.

What does "No credentials found for profile anthropic:default" mean?

It means the system attempted to use the auth profile ID anthropic:default, but could not find credentials for it in the expected auth store.Fix checklist:

Confirm where auth profiles live (new vs legacy paths)
- Current: ~/.pllan/agents/<agentId>/agent/auth-profiles.json
- Legacy: ~/.pllan/agent/* (migrated by pllan doctor)
Confirm your env var is loaded by the Gateway
- If you set ANTHROPIC_API_KEY in your shell but run the Gateway via systemd/launchd, it may not inherit it. Put it in ~/.pllan/.env or enable env.shellEnv.
Make sure you’re editing the correct agent
- Multi-agent setups mean there can be multiple auth-profiles.json files.
Sanity-check model/auth status
- Use pllan models status to see configured models and whether providers are authenticated.

Fix checklist for “No credentials found for profile anthropic”This means the run is pinned to an Anthropic auth profile, but the Gateway can’t find it in its auth store.

Use a setup-token
- Run claude setup-token, then paste it with pllan models auth setup-token --provider anthropic.
- If the token was created on another machine, use pllan models auth paste-token --provider anthropic.
If you want to use an API key instead
- Put ANTHROPIC_API_KEY in ~/.pllan/.env on the gateway host.
- Clear any pinned order that forces a missing profile:
  pllan models auth order clear --provider anthropic
Confirm you’re running commands on the gateway host
- In remote mode, auth profiles live on the gateway machine, not your laptop.

Why did it also try Google Gemini and fail?

If your model config includes Google Gemini as a fallback (or you switched to a Gemini shorthand), Pllan will try it during model fallback. If you haven’t configured Google credentials, you’ll see No API key found for provider "google".Fix: either provide Google auth, or remove/avoid Google models in agents.defaults.model.fallbacks / aliases so fallback doesn’t route there.LLM request rejected: thinking signature required (Google Antigravity)Cause: the session history contains thinking blocks without signatures (often from an aborted/partial stream). Google Antigravity requires signatures for thinking blocks.Fix: Pllan now strips unsigned thinking blocks for Google Antigravity Claude. If it still appears, start a new session or set /thinking off for that agent.

Auth profiles: what they are and how to manage them

Related: /concepts/oauth (OAuth flows, token storage, multi-account patterns)

What is an auth profile?

An auth profile is a named credential record (OAuth or API key) tied to a provider. Profiles live in:

~/.pllan/agents/<agentId>/agent/auth-profiles.json

What are typical profile IDs?

Pllan uses provider-prefixed IDs like:

anthropic:default (common when no email identity exists)
anthropic:<email> for OAuth identities
custom IDs you choose (e.g. anthropic:work)

Can I control which auth profile is tried first?

Yes. Config supports optional metadata for profiles and an ordering per provider (auth.order.<provider>). This does not store secrets; it maps IDs to provider/mode and sets rotation order.Pllan may temporarily skip a profile if it’s in a short cooldown (rate limits/timeouts/auth failures) or a longer disabled state (billing/insufficient credits). To inspect this, run pllan models status --json and check auth.unusableProfiles. Tuning: auth.cooldowns.billingBackoffHours*.You can also set a per-agent order override (stored in that agent’s auth-profiles.json) via the CLI:

# Defaults to the configured default agent (omit --agent)
pllan models auth order get --provider anthropic

# Lock rotation to a single profile (only try this one)
pllan models auth order set --provider anthropic anthropic:default

# Or set an explicit order (fallback within provider)
pllan models auth order set --provider anthropic anthropic:work anthropic:default

# Clear override (fall back to config auth.order / round-robin)
pllan models auth order clear --provider anthropic

To target a specific agent:

pllan models auth order set --provider anthropic --agent main anthropic:default

OAuth vs API key - what is the difference?

Pllan supports both:

OAuth often leverages subscription access (where applicable).
API keys use pay-per-token billing.

The wizard explicitly supports Anthropic setup-token and OpenAI Codex OAuth and can store API keys for you.

Gateway: ports, “already running”, and remote mode

What port does the Gateway use?

gateway.port controls the single multiplexed port for WebSocket + HTTP (Control UI, hooks, etc.).Precedence:

--port > PLLAN_GATEWAY_PORT > gateway.port > default 18789

Why does pllan gateway status say "Runtime: running" but "RPC probe: failed"?

Because “running” is the supervisor’s view (launchd/systemd/schtasks). The RPC probe is the CLI actually connecting to the gateway WebSocket and calling status.Use pllan gateway status and trust these lines:

Probe target: (the URL the probe actually used)
Listening: (what’s actually bound on the port)
Last gateway error: (common root cause when the process is alive but the port isn’t listening)

Why does pllan gateway status show "Config (cli)" and "Config (service)" different?

You’re editing one config file while the service is running another (often a --profile / PLLAN_STATE_DIR mismatch).Fix:

pllan gateway install --force

Run that from the same --profile / environment you want the service to use.

What does "another gateway instance is already listening" mean?

Pllan enforces a runtime lock by binding the WebSocket listener immediately on startup (default ws://127.0.0.1:18789). If the bind fails with EADDRINUSE, it throws GatewayLockError indicating another instance is already listening.Fix: stop the other instance, free the port, or run with pllan gateway --port <port>.

How do I run Pllan in remote mode (client connects to a Gateway elsewhere)?

Set gateway.mode: "remote" and point to a remote WebSocket URL, optionally with a token/password:

{
  gateway: {
    mode: "remote",
    remote: {
      url: "ws://gateway.tailnet:18789",
      token: "your-token",
      password: "your-password",
    },
  },
}

Notes:

pllan gateway only starts when gateway.mode is local (or you pass the override flag).
The macOS app watches the config file and switches modes live when these values change.

The Control UI says "unauthorized" (or keeps reconnecting). What now?

Your gateway is running with auth enabled (gateway.auth.*), but the UI is not sending the matching token/password.Facts (from code):

The Control UI keeps the token in sessionStorage for the current browser tab session and selected gateway URL, so same-tab refreshes keep working without restoring long-lived localStorage token persistence.
On AUTH_TOKEN_MISMATCH, trusted clients can attempt one bounded retry with a cached device token when the gateway returns retry hints (canRetryWithDeviceToken=true, recommendedNextStep=retry_with_device_token).

Fix:

Fastest: pllan dashboard (prints + copies the dashboard URL, tries to open; shows SSH hint if headless).
If you don’t have a token yet: pllan doctor --generate-gateway-token.
If remote, tunnel first: ssh -N -L 18789:127.0.0.1:18789 user@host then open http://127.0.0.1:18789/.
Set gateway.auth.token (or PLLAN_GATEWAY_TOKEN) on the gateway host.
In the Control UI settings, paste the same token.
If mismatch persists after the one retry, rotate/re-approve the paired device token:
- pllan devices list
- pllan devices rotate --device <id> --role operator
Still stuck? Run pllan status --all and follow Troubleshooting. See Dashboard for auth details.

I set gateway.bind tailnet but it cannot bind and nothing listens

tailnet bind picks a Tailscale IP from your network interfaces (100.64.0.0/10). If the machine isn’t on Tailscale (or the interface is down), there’s nothing to bind to.Fix:

Start Tailscale on that host (so it has a 100.x address), or
Switch to gateway.bind: "loopback" / "lan".

Note: tailnet is explicit. auto prefers loopback; use gateway.bind: "tailnet" when you want a tailnet-only bind.

Can I run multiple Gateways on the same host?

Usually no - one Gateway can run multiple messaging channels and agents. Use multiple Gateways only when you need redundancy (ex: rescue bot) or hard isolation.Yes, but you must isolate:

PLLAN_CONFIG_PATH (per-instance config)
PLLAN_STATE_DIR (per-instance state)
agents.defaults.workspace (workspace isolation)
gateway.port (unique ports)

Quick setup (recommended):

Use pllan --profile <name> ... per instance (auto-creates ~/.pllan-<name>).
Set a unique gateway.port in each profile config (or pass --port for manual runs).
Install a per-profile service: pllan --profile <name> gateway install.

Profiles also suffix service names (ai.pllan.<profile>; legacy com.pllan.*, pllan-gateway-<profile>.service, Pllan Gateway (<profile>)). Full guide: Multiple gateways.

What does "invalid handshake" / code 1008 mean?

The Gateway is a WebSocket server, and it expects the very first message to be a connect frame. If it receives anything else, it closes the connection with code 1008 (policy violation).Common causes:

You opened the HTTP URL in a browser (http://...) instead of a WS client.
You used the wrong port or path.
A proxy or tunnel stripped auth headers or sent a non-Gateway request.

Quick fixes:

Use the WS URL: ws://<host>:18789 (or wss://... if HTTPS).
Don’t open the WS port in a normal browser tab.
If auth is on, include the token/password in the connect frame.

If you’re using the CLI or TUI, the URL should look like:

pllan tui --url ws://<host>:18789 --token <token>

Protocol details: Gateway protocol.

Logging and debugging

Where are logs?

File logs (structured):

/tmp/pllan/pllan-YYYY-MM-DD.log

You can set a stable path via logging.file. File log level is controlled by logging.level. Console verbosity is controlled by --verbose and logging.consoleLevel.Fastest log tail:

pllan logs --follow

Service/supervisor logs (when the gateway runs via launchd/systemd):

macOS: $PLLAN_STATE_DIR/logs/gateway.log and gateway.err.log (default: ~/.pllan/logs/...; profiles use ~/.pllan-<profile>/logs/...)
Linux: journalctl --user -u pllan-gateway[-<profile>].service -n 200 --no-pager
Windows: schtasks /Query /TN "Pllan Gateway (<profile>)" /V /FO LIST

See Troubleshooting for more.

How do I start/stop/restart the Gateway service?

Use the gateway helpers:

pllan gateway status
pllan gateway restart

If you run the gateway manually, pllan gateway --force can reclaim the port. See Gateway.

I closed my terminal on Windows - how do I restart Pllan?

There are two Windows install modes:1) WSL2 (recommended): the Gateway runs inside Linux.Open PowerShell, enter WSL, then restart:

wsl
pllan gateway status
pllan gateway restart

If you never installed the service, start it in the foreground:

pllan gateway run

2) Native Windows (not recommended): the Gateway runs directly in Windows.Open PowerShell and run:

pllan gateway status
pllan gateway restart

If you run it manually (no service), use:

pllan gateway run

Docs: Windows (WSL2), Gateway service runbook.

The Gateway is up but replies never arrive. What should I check?

Start with a quick health sweep:

pllan status
pllan models status
pllan channels status
pllan logs --follow

Common causes:

Model auth not loaded on the gateway host (check models status).
Channel pairing/allowlist blocking replies (check channel config + logs).
WebChat/Dashboard is open without the right token.

If you are remote, confirm the tunnel/Tailscale connection is up and that the Gateway WebSocket is reachable.Docs: Channels, Troubleshooting, Remote access.

"Disconnected from gateway: no reason" - what now?

This usually means the UI lost the WebSocket connection. Check:

Is the Gateway running? pllan gateway status
Is the Gateway healthy? pllan status
Does the UI have the right token? pllan dashboard
If remote, is the tunnel/Tailscale link up?

Then tail logs:

pllan logs --follow

Docs: Dashboard, Remote access, Troubleshooting.

Telegram setMyCommands fails. What should I check?

Start with logs and channel status:

pllan channels status
pllan channels logs --channel telegram

Then match the error:

BOT_COMMANDS_TOO_MUCH: the Telegram menu has too many entries. Pllan already trims to the Telegram limit and retries with fewer commands, but some menu entries still need to be dropped. Reduce plugin/skill/custom commands, or disable channels.telegram.commands.native if you do not need the menu.
TypeError: fetch failed, Network request for 'setMyCommands' failed!, or similar network errors: if you are on a VPS or behind a proxy, confirm outbound HTTPS is allowed and DNS works for api.telegram.org.

If the Gateway is remote, make sure you are looking at logs on the Gateway host.Docs: Telegram, Channel troubleshooting.

TUI shows no output. What should I check?

First confirm the Gateway is reachable and the agent can run:

pllan status
pllan models status
pllan logs --follow

In the TUI, use /status to see the current state. If you expect replies in a chat channel, make sure delivery is enabled (/deliver on).Docs: TUI, Slash commands.

How do I completely stop then start the Gateway?

If you installed the service:

pllan gateway stop
pllan gateway start

This stops/starts the supervised service (launchd on macOS, systemd on Linux). Use this when the Gateway runs in the background as a daemon.If you’re running in the foreground, stop with Ctrl-C, then:

pllan gateway run

Docs: Gateway service runbook.

ELI5: pllan gateway restart vs pllan gateway

pllan gateway restart: restarts the background service (launchd/systemd).
pllan gateway: runs the gateway in the foreground for this terminal session.

If you installed the service, use the gateway commands. Use pllan gateway when you want a one-off, foreground run.

Fastest way to get more details when something fails

Start the Gateway with --verbose to get more console detail. Then inspect the log file for channel auth, model routing, and RPC errors.

Media and attachments

My skill generated an image/PDF, but nothing was sent

Outbound attachments from the agent must include a MEDIA:<path-or-url> line (on its own line). See Pllan assistant setup and Agent send.CLI sending:

pllan message send --target +15555550123 --message "Here you go" --media /path/to/file.png

Also check:

The target channel supports outbound media and isn’t blocked by allowlists.
The file is within the provider’s size limits (images are resized to max 2048px).

See Images.

Security and access control

Is it safe to expose Pllan to inbound DMs?

Treat inbound DMs as untrusted input. Defaults are designed to reduce risk:

Default behavior on DM-capable channels is pairing:
- Unknown senders receive a pairing code; the bot does not process their message.
- Approve with: pllan pairing approve --channel <channel> [--account <id>] <code>
- Pending requests are capped at 3 per channel; check pllan pairing list --channel <channel> [--account <id>] if a code didn’t arrive.
Opening DMs publicly requires explicit opt-in (dmPolicy: "open" and allowlist "*").

Run pllan doctor to surface risky DM policies.

Is prompt injection only a concern for public bots?

No. Prompt injection is about untrusted content, not just who can DM the bot. If your assistant reads external content (web search/fetch, browser pages, emails, docs, attachments, pasted logs), that content can include instructions that try to hijack the model. This can happen even if you are the only sender.The biggest risk is when tools are enabled: the model can be tricked into exfiltrating context or calling tools on your behalf. Reduce the blast radius by:

using a read-only or tool-disabled “reader” agent to summarize untrusted content
keeping web_search / web_fetch / browser off for tool-enabled agents
sandboxing and strict tool allowlists

Details: Security.

Should my bot have its own email, GitHub account, or phone number?

Yes, for most setups. Isolating the bot with separate accounts and phone numbers reduces the blast radius if something goes wrong. This also makes it easier to rotate credentials or revoke access without impacting your personal accounts.Start small. Give access only to the tools and accounts you actually need, and expand later if required.Docs: Security, Pairing.

Can I give it autonomy over my text messages and is that safe?

We do not recommend full autonomy over your personal messages. The safest pattern is:

Keep DMs in pairing mode or a tight allowlist.
Use a separate number or account if you want it to message on your behalf.
Let it draft, then approve before sending.

If you want to experiment, do it on a dedicated account and keep it isolated. See Security.

Can I use cheaper models for personal assistant tasks?

Yes, if the agent is chat-only and the input is trusted. Smaller tiers are more susceptible to instruction hijacking, so avoid them for tool-enabled agents or when reading untrusted content. If you must use a smaller model, lock down tools and run inside a sandbox. See Security.

I ran /start in Telegram but did not get a pairing code

Pairing codes are sent only when an unknown sender messages the bot and dmPolicy: "pairing" is enabled. /start by itself doesn’t generate a code.Check pending requests:

pllan pairing list telegram

If you want immediate access, allowlist your sender id or set dmPolicy: "open" for that account.

WhatsApp: will it message my contacts? How does pairing work?

No. Default WhatsApp DM policy is pairing. Unknown senders only get a pairing code and their message is not processed. Pllan only replies to chats it receives or to explicit sends you trigger.Approve pairing with:

pllan pairing approve whatsapp <code>

List pending requests:

pllan pairing list whatsapp

Wizard phone number prompt: it’s used to set your allowlist/owner so your own DMs are permitted. It’s not used for auto-sending. If you run on your personal WhatsApp number, use that number and enable channels.whatsapp.selfChatMode.

Chat commands, aborting tasks, and “it will not stop”

How do I stop internal system messages from showing in chat?

Most internal or tool messages only appear when verbose or reasoning is enabled for that session.Fix in the chat where you see it:

/verbose off
/reasoning off

If it is still noisy, check the session settings in the Control UI and set verbose to inherit. Also confirm you are not using a bot profile with verboseDefault set to on in config.Docs: Thinking and verbose, Security.

How do I stop/cancel a running task?

Send any of these as a standalone message (no slash):

stop
stop action
stop current action
stop run
stop current run
stop agent
stop the agent
stop pllan
pllan stop
stop don't do anything
stop do not do anything
stop doing anything
please stop
stop please
abort
esc
wait
exit
interrupt

These are abort triggers (not slash commands).For background processes (from the exec tool), you can ask the agent to run:

process action:kill sessionId:XXX

Slash commands overview: see Slash commands.Most commands must be sent as a standalone message that starts with /, but a few shortcuts (like /status) also work inline for allowlisted senders.

How do I send a Discord message from Telegram? ("Cross-context messaging denied")

Pllan blocks cross-provider messaging by default. If a tool call is bound to Telegram, it won’t send to Discord unless you explicitly allow it.Enable cross-provider messaging for the agent:

{
  agents: {
    defaults: {
      tools: {
        message: {
          crossContext: {
            allowAcrossProviders: true,
            marker: { enabled: true, prefix: "[from {channel}] " },
          },
        },
      },
    },
  },
}

Restart the gateway after editing config. If you only want this for a single agent, set it under agents.list[].tools.message instead.

Why does it feel like the bot "ignores" rapid-fire messages?

Queue mode controls how new messages interact with an in-flight run. Use /queue to change modes:

steer - new messages redirect the current task
followup - run messages one at a time
collect - batch messages and reply once (default)
steer-backlog - steer now, then process backlog
interrupt - abort current run and start fresh

You can add options like debounce:2s cap:25 drop:summarize for followup modes.

Miscellaneous

What is the default model for Anthropic with an API key?

In Pllan, credentials and model selection are separate. Setting ANTHROPIC_API_KEY (or storing an Anthropic API key in auth profiles) enables authentication, but the actual default model is whatever you configure in agents.defaults.model.primary (for example, anthropic/claude-sonnet-4-6 or anthropic/claude-opus-4-6). If you see No credentials found for profile "anthropic:default", it means the Gateway couldn’t find Anthropic credentials in the expected auth-profiles.json for the agent that’s running.

Still stuck? Ask in Discord or open a GitHub discussion.

Help

Community

Environment and debugging

Compaction internals

Developer setup

Contributing

Docs meta

FAQ

FAQ

First 60 seconds if something is broken

Quick start and first-run setup

What is Pllan?

Skills and automation

Sandboxing and memory

Where things live on disk

Config basics

Remote gateways and nodes

Env vars and .env loading

Sessions and multiple chats

Models: defaults, selection, aliases, switching

Model failover and “All models failed”

Auth profiles: what they are and how to manage them

Gateway: ports, “already running”, and remote mode

Logging and debugging

Media and attachments

Security and access control

Chat commands, aborting tasks, and “it will not stop”

Miscellaneous

Help

Community

Environment and debugging

Compaction internals

Developer setup

Contributing

Docs meta

​FAQ

​First 60 seconds if something is broken

​Quick start and first-run setup

​What is Pllan?

​Skills and automation

​Sandboxing and memory

​Where things live on disk

​Config basics

​Remote gateways and nodes

​Env vars and .env loading

​Sessions and multiple chats

​Models: defaults, selection, aliases, switching

​Model failover and “All models failed”

​Auth profiles: what they are and how to manage them

​Gateway: ports, “already running”, and remote mode

​Logging and debugging

​Media and attachments

​Security and access control

​Chat commands, aborting tasks, and “it will not stop”

​Miscellaneous

FAQ

First 60 seconds if something is broken

Quick start and first-run setup

What is Pllan?

Skills and automation

Sandboxing and memory

Where things live on disk

Config basics

Remote gateways and nodes

Env vars and .env loading

Sessions and multiple chats

Models: defaults, selection, aliases, switching

Model failover and “All models failed”

Auth profiles: what they are and how to manage them

Gateway: ports, “already running”, and remote mode

Logging and debugging

Media and attachments

Security and access control

Chat commands, aborting tasks, and “it will not stop”

Miscellaneous