Auto-chaining was removed from the codebase. All docs now describe the scheduling model: work_finish transitions labels, the heartbeat's tick pass (which also fires immediately after every work_finish) detects available work and fills free slots. Removed autoChain config references. Files updated: README.md, README2.md, docs/TOOLS.md, ARCHITECTURE.md, ROADMAP.md, MANAGEMENT.md, ONBOARDING.md, lib/templates.ts https://claude.ai/code/session_01R3rGevPY748gP4uK2ggYag
252 lines
9.5 KiB
Markdown
252 lines
9.5 KiB
Markdown
# DevClaw — Onboarding Guide
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Step-by-step setup: install the plugin, configure an agent, register projects, and run your first task.
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## Prerequisites
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| Requirement | Why | How to check |
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| [OpenClaw](https://openclaw.ai) installed | DevClaw is an OpenClaw plugin | `openclaw --version` |
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| Node.js >= 20 | Runtime for plugin | `node --version` |
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| [`gh`](https://cli.github.com) or [`glab`](https://gitlab.com/gitlab-org/cli) CLI | Issue tracker provider (auto-detected from git remote) | `gh --version` or `glab --version` |
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| CLI authenticated | Plugin calls gh/glab for every label transition | `gh auth status` or `glab auth status` |
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| A GitHub/GitLab repo with issues | The task backlog lives in the issue tracker | `gh issue list` or `glab issue list` from your repo |
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## Step 1: Install the plugin
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```bash
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# Copy to extensions directory (auto-discovered on next restart)
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cp -r devclaw ~/.openclaw/extensions/
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```
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Verify:
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```bash
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openclaw plugins list
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# Should show: DevClaw | devclaw | loaded
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```
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## Step 2: Run setup
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There are three ways to set up DevClaw:
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### Option A: Conversational onboarding (recommended)
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Call the `onboard` tool from any agent that has the DevClaw plugin loaded. The agent walks you through configuration step by step — asking about:
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- Agent selection (current or create new)
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- Channel binding (telegram/whatsapp/none) — for new agents only
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- Model levels (accept defaults or customize)
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- Optional project registration
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The tool returns instructions that guide the agent through the QA-style setup conversation.
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### Option B: CLI wizard
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```bash
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openclaw devclaw setup
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```
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The setup wizard walks you through:
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1. **Agent** — Create a new orchestrator agent or configure an existing one
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2. **Developer team** — Choose which LLM model powers each developer level:
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- **DEV junior** (fast, cheap tasks) — default: `anthropic/claude-haiku-4-5`
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- **DEV medior** (standard tasks) — default: `anthropic/claude-sonnet-4-5`
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- **DEV senior** (complex tasks) — default: `anthropic/claude-opus-4-5`
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- **QA reviewer** (code review) — default: `anthropic/claude-sonnet-4-5`
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- **QA tester** (manual testing) — default: `anthropic/claude-haiku-4-5`
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3. **Workspace** — Writes AGENTS.md, HEARTBEAT.md, role templates, and initializes state
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Non-interactive mode:
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```bash
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# Create new agent with default models
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openclaw devclaw setup --new-agent "My Dev Orchestrator"
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# Configure existing agent with custom models
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openclaw devclaw setup --agent my-orchestrator \
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--junior "anthropic/claude-haiku-4-5" \
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--senior "anthropic/claude-opus-4-5"
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```
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### Option C: Tool call (agent-driven)
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**Conversational onboarding via tool:**
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```json
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onboard({ "mode": "first-run" })
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```
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The tool returns step-by-step instructions that guide the agent through the setup conversation.
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**Direct setup (skip conversation):**
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```json
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setup({
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"newAgentName": "My Dev Orchestrator",
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"channelBinding": "telegram",
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"models": {
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"dev": {
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"junior": "anthropic/claude-haiku-4-5",
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"senior": "anthropic/claude-opus-4-5"
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},
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"qa": {
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"reviewer": "anthropic/claude-sonnet-4-5"
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}
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}
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})
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```
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## Step 3: Channel binding (optional, for new agents)
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If you created a new agent during conversational onboarding and selected a channel binding (telegram/whatsapp), the agent is automatically bound. **Skip to step 4.**
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**Smart Migration**: If an existing agent already has a channel-wide binding (e.g., the old orchestrator receives all telegram messages), the onboarding agent will:
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1. Detect the conflict
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2. Ask if you want to migrate the binding from the old agent to the new one
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3. If you confirm, the binding is automatically moved — no manual config edit needed
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If you didn't bind a channel during setup:
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**Option A: Manually edit `openclaw.json`**
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```json
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{
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"bindings": [
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{
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"agentId": "my-orchestrator",
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"match": {
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"channel": "telegram"
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}
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}
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]
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}
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```
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For group-specific bindings:
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```json
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{
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"agentId": "my-orchestrator",
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"match": {
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"channel": "telegram",
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"peer": {
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"kind": "group",
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"id": "-1234567890"
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}
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}
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}
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```
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Restart OpenClaw after editing.
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**Option B: Add bot to Telegram/WhatsApp group**
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If using a channel-wide binding (no peer filter), the agent receives all messages from that channel. Add your orchestrator bot to the relevant Telegram group.
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## Step 4: Register your project
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Go to the Telegram/WhatsApp group for the project and tell the orchestrator agent:
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> "Register project my-project at ~/git/my-project with base branch development"
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The agent calls `project_register`, which atomically:
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- Validates the repo and auto-detects GitHub/GitLab from remote
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- Creates all 8 state labels (idempotent)
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- Scaffolds role instruction files (`projects/roles/<project>/dev.md` and `qa.md`)
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- Adds the project entry to `projects.json`
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- Logs the registration event
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**Initial state in `projects.json`:**
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```json
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{
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"projects": {
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"-1234567890": {
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"name": "my-project",
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"repo": "~/git/my-project",
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"groupName": "Project: my-project",
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"baseBranch": "development",
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"deployBranch": "development",
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"channel": "telegram",
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"roleExecution": "parallel",
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"dev": {
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"active": false,
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"issueId": null,
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"startTime": null,
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"level": null,
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"sessions": { "junior": null, "medior": null, "senior": null }
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},
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"qa": {
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"active": false,
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"issueId": null,
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"startTime": null,
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"level": null,
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"sessions": { "reviewer": null, "tester": null }
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}
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}
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}
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}
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```
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**Finding the Telegram group ID:** The group ID is the numeric ID of your Telegram supergroup (a negative number like `-1234567890`). When you call `project_register` from within the group, the ID is auto-detected from context.
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## Step 5: Create your first issue
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Issues can be created in multiple ways:
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- **Via the agent** — Ask the orchestrator in the Telegram group: "Create an issue for adding a login page" (uses `task_create`)
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- **Via workers** — DEV/QA workers can call `task_create` to file follow-up bugs they discover
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- **Via CLI** — `cd ~/git/my-project && gh issue create --title "My first task" --label "To Do"` (or `glab issue create`)
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- **Via web UI** — Create an issue and add the "To Do" label
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Note: `task_create` defaults to the "Planning" label. Use "To Do" explicitly when the task is ready for immediate work.
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## Step 6: Test the pipeline
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Ask the agent in the Telegram group:
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> "Check the queue status"
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The agent should call `status` and report the "To Do" issue. Then:
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> "Pick up issue #1 for DEV"
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The agent calls `work_start`, which assigns a developer level, transitions the label to "Doing", creates or reuses a worker session, and dispatches the task — all in one call. The agent posts the announcement.
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## Adding more projects
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Tell the agent to register a new project (step 4) from within the new project's Telegram group. That's it — `project_register` handles labels and state setup.
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Each project is fully isolated — separate queue, separate workers, separate state.
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## Developer levels
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DevClaw assigns tasks to developer levels instead of raw model names. This makes the system intuitive — you're assigning a "junior dev" to fix a typo, not configuring model parameters.
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| Role | Level | Default model | When to assign |
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|------|-------|---------------|----------------|
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| DEV | **junior** | `anthropic/claude-haiku-4-5` | Typos, single-file fixes, CSS changes |
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| DEV | **medior** | `anthropic/claude-sonnet-4-5` | Features, bug fixes, multi-file changes |
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| DEV | **senior** | `anthropic/claude-opus-4-5` | Architecture, migrations, system-wide refactoring |
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| QA | **reviewer** | `anthropic/claude-sonnet-4-5` | Code review, test validation |
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| QA | **tester** | `anthropic/claude-haiku-4-5` | Manual testing, smoke tests |
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Change which model powers each level in `openclaw.json` — see [Configuration](CONFIGURATION.md#model-tiers).
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## What the plugin handles vs. what you handle
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| Responsibility | Who | Details |
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| Plugin installation | You (once) | `cp -r devclaw ~/.openclaw/extensions/` |
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| Agent + workspace setup | Plugin (`setup`) | Creates agent, configures models, writes workspace files |
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| Channel binding migration | Plugin (`setup` with `migrateFrom`) | Automatically moves channel-wide bindings between agents |
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| Label setup | Plugin (`project_register`) | 8 labels, created idempotently via IssueProvider |
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| Prompt file scaffolding | Plugin (`project_register`) | Creates `projects/roles/<project>/dev.md` and `qa.md` |
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| Project registration | Plugin (`project_register`) | Entry in `projects.json` with empty worker state |
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| Telegram group setup | You (once per project) | Add bot to group |
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| Issue creation | Plugin (`task_create`) | Orchestrator or workers create issues from chat |
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| Label transitions | Plugin | Atomic transitions via issue tracker CLI |
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| Developer assignment | Plugin | LLM-selected level by orchestrator, keyword heuristic fallback |
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| State management | Plugin | Atomic read/write to `projects.json` |
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| Session management | Plugin | Creates, reuses, and dispatches to sessions via CLI. Agent never touches session tools. |
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| Task completion | Plugin (`work_finish`) | Workers self-report. Scheduler dispatches next role. |
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| Prompt instructions | Plugin (`work_start`) | Loaded from `projects/roles/<project>/<role>.md`, appended to task message |
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| Audit logging | Plugin | Automatic NDJSON append per tool call |
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| Zombie detection | Plugin | `health` checks active vs alive |
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| Queue scanning | Plugin | `status` queries issue tracker per project |
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