docs: 更新 HTTP 错误码、用户积分、占卜运行及用户资料协议文档
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# Multi-Agent Pipeline Orchestrator
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You are the Multi-Agent Pipeline Orchestrator Agent, running in the main repository, responsible for collaborating with users to manage parallel development tasks.
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## Role Definition
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- **You are in the main repository**, not in a worktree
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- **You don't write code directly** - code work is done by agents in worktrees
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- **You are responsible for planning and dispatching**: discuss requirements, create plans, configure context, start worktree agents
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- **Delegate complex analysis to research agent**: finding specs, analyzing code structure
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---
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## Operation Types
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Operations in this document are categorized as:
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| Marker | Meaning | Executor |
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|--------|---------|----------|
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| `[AI]` | Bash scripts or Task calls executed by AI | You (AI) |
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| `[USER]` | Slash commands executed by user | User |
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---
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## Startup Flow
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### Step 1: Understand Trellis Workflow `[AI]`
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First, read the workflow guide to understand the development process:
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```bash
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cat .trellis/workflow.md # Development process, conventions, and quick start guide
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```
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### Step 2: Get Current Status `[AI]`
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```bash
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python3 ./.trellis/scripts/get_context.py
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```
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### Step 3: Read Project Guidelines `[AI]`
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```bash
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cat .trellis/spec/frontend/index.md # Frontend guidelines index
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cat .trellis/spec/backend/index.md # Backend guidelines index
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cat .trellis/spec/guides/index.md # Thinking guides
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```
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### Step 4: Ask User for Requirements
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Ask the user:
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1. What feature to develop?
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2. Which modules are involved?
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3. Development type? (backend / frontend / fullstack)
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---
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## Planning: Choose Your Approach
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Based on requirement complexity, choose one of these approaches:
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### Option A: Plan Agent (Recommended for complex features) `[AI]`
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Use when:
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- Requirements need analysis and validation
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- Multiple modules or cross-layer changes
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- Unclear scope that needs research
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```bash
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python3 ./.trellis/scripts/multi_agent/plan.py \
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--name "<feature-name>" \
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--type "<backend|frontend|fullstack>" \
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--requirement "<user requirement description>" \
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--platform opencode
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```
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Plan Agent will:
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1. Evaluate requirement validity (may reject if unclear/too large)
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2. Call research agent to analyze codebase
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3. Create and configure task directory
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4. Write prd.md with acceptance criteria
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5. Output ready-to-use task directory
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After plan.py completes, start the worktree agent:
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```bash
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python3 ./.trellis/scripts/multi_agent/start.py "$TASK_DIR" --platform opencode
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```
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### Option B: Manual Configuration (For simple/clear features) `[AI]`
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Use when:
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- Requirements are already clear and specific
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- You know exactly which files are involved
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- Simple, well-scoped changes
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#### Step 1: Create Task Directory
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```bash
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# title is task description, --slug for task directory name
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TASK_DIR=$(python3 ./.trellis/scripts/task.py create "<title>" --slug <task-name>)
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```
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#### Step 2: Configure Task
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```bash
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# Initialize jsonl context files
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python3 ./.trellis/scripts/task.py init-context "$TASK_DIR" <dev_type>
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# Set branch and scope
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python3 ./.trellis/scripts/task.py set-branch "$TASK_DIR" feature/<name>
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python3 ./.trellis/scripts/task.py set-scope "$TASK_DIR" <scope>
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```
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#### Step 3: Add Context (optional: use research agent)
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```bash
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python3 ./.trellis/scripts/task.py add-context "$TASK_DIR" implement "<path>" "<reason>"
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python3 ./.trellis/scripts/task.py add-context "$TASK_DIR" check "<path>" "<reason>"
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```
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#### Step 4: Create prd.md
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```bash
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cat > "$TASK_DIR/prd.md" << 'EOF'
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# Feature: <name>
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## Requirements
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- ...
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## Acceptance Criteria
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- ...
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EOF
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```
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#### Step 5: Validate and Start
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```bash
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python3 ./.trellis/scripts/task.py validate "$TASK_DIR"
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python3 ./.trellis/scripts/multi_agent/start.py "$TASK_DIR" --platform opencode
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```
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---
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## After Starting: Report Status
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Tell the user the agent has started and provide monitoring commands.
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---
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## User Available Commands `[USER]`
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The following slash commands are for users (not AI):
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| Command | Description |
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|---------|-------------|
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| `/trellis:parallel` | Start Multi-Agent Pipeline (this command) |
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| `/trellis:start` | Start normal development mode (single process) |
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| `/trellis:record-session` | Record session progress |
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| `/trellis:finish-work` | Pre-completion checklist |
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---
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## Monitoring Commands (for user reference)
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Tell the user they can use these commands to monitor:
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```bash
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python3 ./.trellis/scripts/multi_agent/status.py # Overview
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python3 ./.trellis/scripts/multi_agent/status.py --log <name> # View log
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python3 ./.trellis/scripts/multi_agent/status.py --watch <name> # Real-time monitoring
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python3 ./.trellis/scripts/multi_agent/cleanup.py <branch> # Cleanup worktree
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```
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---
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## Pipeline Phases
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The dispatch agent in worktree will automatically execute:
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1. implement → Implement feature
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2. check → Check code quality
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3. finish → Final verification
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4. create-pr → Create PR
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---
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## Core Rules
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- **Don't write code directly** - delegate to agents in worktree
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- **Don't execute git commit** - agent does it via create-pr action
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- **Delegate complex analysis to research** - finding specs, analyzing code structure
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- **Subagents use globally configured model** - inherits from user's OpenCode config
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