以 AI 机器人身份加入视频会议,提供语音、虚拟形象与屏幕共享四种模式。
记忆
deep-coding-p
试用Advanced multi-agent development system for complex software projects. Leverages Orchestrator, Builder, and Reviewer agents to decompose modules, implement c...
它能做什么
This skill requires the following system capabilities:
技能文档
System Dependencies
This skill requires the following system capabilities:
| Dependency | Purpose | Required? | Check |
|---|---|---|---|
python3 | Dashboard server (port 8765) | Yes | python3 --version |
node / npm | Project builds, Playwright | For web projects | node -v, npm -v |
playwright | E2E browser testing (Reviewers) | Optional, for E2E | npx playwright --version |
| ACP runtime | Builder/Reviewer agent execution | Optional, see below | Platform-specific |
No specific coding agent is required. The default configuration uses ACP + qoder, but you can use any available agent runtime. See First-Time Setup for configuration options.
Security Notes
⚠️ Dashboard server (server.py):
- Binds to
127.0.0.1:8765only — never expose to public network - Serves files from the project directory — verify no secrets (API keys, tokens) are present
- Includes path traversal protection via
safe_path()check
⚠️ Code execution:
- Builders and Reviewers will execute and run arbitrary project code
- For web projects: HTTP server serves project files locally
- E2E tests use Playwright to open and interact with pages in a real browser
- Only run on machines where executing generated code is acceptable
- Use containers/VMs for untrusted projects
First-Time Setup
When a user installs this skill for the first time, guide them through the following steps:
Step 1: Create Project Workspace
mkdir -p my-projects/{requests/done,logs}
cp /assets/server.py my-projects/
cp /assets/dashboard.html my-projects/
cd my-projects
This creates the project root with all required directories and the Dashboard assets.
Step 2: Configure Orchestrator Agent
Create an Orchestrator agent in your openclaw.json (or equivalent config):
{
"id": "orchestrator",
"name": "Orchestrator",
"workspace": "/my-projects"
}
Give the Orchestrator a heartbeat prompt that references references/orchestrator-rules.md.
Step 3: Configure Builder Agent(s)
Choose your preferred coding agent(s). Options:
| Option | Configuration | Notes |
|---|---|---|
| ACP + qoder | runtime: "acp", agentId: "qoder" | Default, requires acpx plugin |
| ACP + claude | runtime: "acp", agentId: "claude" | Alternative ACP agent |
| ACP + codex | runtime: "acp", agentId: "codex" | OpenAI Codex |
| Subagent runtime | runtime: "subagent" | Built-in, no extra setup |
| PTY coding agents | exec with PTY | Claude Code, Codex CLI, etc. |
The Orchestrator rules (references/orchestrator-rules.md) default to ACP + qoder, but you should update the agent ID to match your setup.
Recommended: Set up a 3-tier fallback chain
- Primary: Your preferred coding agent (e.g., qoder, claude)
- Fallback 1: Alternative ACP agent (e.g., claude if qoder is 429'd)
- Fallback 2: Built-in subagent runtime
Step 4: Allow Tool Access
Ensure your Orchestrator and Builder agents have access to:
read,write,edit— for file operationsexec— for running builds, tests, serverssessions_spawn,sessions_send,sessions_list— for agent communicationsubagents— for managing spawned agents
In openclaw.json:
{
"tools": {
"sessions": {
"visibility": "all"
},
"agentToAgent": {
"enabled": true,
"allow": ["main", "orchestrator", "qoder-dev", "claude-dev"]
}
},
"acp": {
"enabled": true,
"backend": "acpx",
"defaultAgent": "qoder",
"allowedAgents": ["qoder", "claude", "codex"]
}
}
Step 5: Choose Your LLM
Set the default model for the Orchestrator and agents:
{
"agents": {
"defaults": {
"model": {
"primary": "your-provider/your-model"
}
}
}
}
For coding agents (qoder, claude, codex), they use their own model — no LLM config needed.
Step 6: Verify Setup
cd my-projects
python3 server.py
# Open http://localhost:8765 — should show empty dashboard
Harness Deep Coding System
Multi-agent development: Orchestrator decomposes → Builders code → Reviewers verify → E2E test → deliver.
Roles
User-Facing Agent (you)
- Gather requirements through conversation
- Create request JSON at
projects/requests/TIMESTAMP.json(use actual timestamp) - Notify Orchestrator via
sessions_sendtoagent:orchestrator:main - Report progress every heartbeat when project is active
Orchestrator
- Decomposes project into 2-4 modules + mandatory integration-test
- Creates
project-state.jsonwith module states - Spawns Builders and Reviewers via
sessions_spawn - Monitors progress via heartbeat, handles failures
- Runs E2E smoke test after bugfix/feature accepted
Builder
- Codes independently per module
- Uses configured agent runtime (ACP subagent, or fallback)
- Writes to
logs/builder-MODULE.log(APPEND, UTC+8)
Reviewer
- MUST actually test the application, not just read code
- For web projects: serve via HTTP, verify in browser
- Writes detailed review results to
review_history - Writes to
logs/reviewer-MODULE.log(APPEND, UTC+8)
User-Facing Workflow
1. Gather Requirements
- What to build, key features, constraints, tech stack
- Break into 2-4 logical modules (data → core → render → UI)
- Auto-add final
integration-testmodule depending on ALL others
2. Create Request
{
"name": "Project Name",
"description": "What it does",
"owner": "user name",
"tags": ["web", "game"]
}
Path: /requests/TIMESTAMP.json (use actual timestamp)
3. Notify Orchestrator
Send to agent:orchestrator:main:
- Request file path
- Instructions to decompose into modules
- Create project-state.json
- Spawn Builder for first module
- Use per-agent logs, APPEND mode, UTC+8
- Run E2E smoke test after acceptance
4. Progress Reporting
Read project-state.json every heartbeat:
- Report completion % and module states
- Announce 100% completion
Project Structure
All paths are relative to your project root directory:
/
├── projects-registry.json ← All projects overview
├── server.py ← Dashboard server (port 8765)
├── dashboard.html ← Dashboard UI
├── requests/
│ └── done/ ← Processed requests
├── logs/ ← Agent activity logs
├── PROJECT-SLUG/
│ ├── project-state.json ← Module states, review history
│ ├── logs/
│ │ ├── orchestrator.log ← Orchestrator decisions
│ │ ├── builder-MODULE.log ← Each Builder writes own file
│ │ └── reviewer-MODULE.log ← Each Reviewer writes own file
│ └── SOURCE CODE (generated files)
See references/architecture.md for full project structure, module lifecycle, and dashboard details.
Module Lifecycle
pending → in_progress → ready_for_review → in_review → accepted
↑ |
└── needs_revision ──┘
Critical Rules
| Rule | Description |
|---|---|
| One action per heartbeat | Never do multiple spawns in one cycle |
| Spawn Reviewer immediately | Never leave ready_for_review more than one cycle |
| Reviewer writes results | Must write to review_history array, never just change state |
| E2E smoke test | Mandatory for bugfixes and new features before delivery |
| No archive copies | DO NOT copy project-state.json to archive/ |
Common Issues
| Issue | Fix |
|---|---|
| 429 rate limit | Wait, then re-spawn. Do NOT self-accept |
| Missing E2E | Bugfix/feature accepted → must spawn E2E Reviewer |
| Reviewer not spawned | Check sessions_list, spawn if missing |
| Builder timeout | Check if files exist, accept if complete |
| Archive duplicates | Orchestrator should NOT copy to archive/ |
Dashboard
Dashboard is included in assets/server.py and assets/dashboard.html.
Usage:
- Copy
assets/server.pyandassets/dashboard.htmlto your project root directory - Run:
python3 server.py - Open:
http://localhost:8765
Security: The server binds to 127.0.0.1 only and includes path traversal protection.
Features: project list, completion status, module states, agent activity timeline.
相关技能
把自然语言描述转为结构化 JSON,并由 mcp-diagram-generator MCP 服务生成 Draw.io、Mermaid 或 Excalidraw 图表文件。
在本地磁盘以分类纯 Markdown 文件保存需要长期留存的事实,与智能体内置记忆并存。
诊断生产力系统反复失效的根因,给出最小干预——容量测算、瓶颈定位、可靠的本地记录。
按用户明确指令,在得到大脑(Get笔记)中保存、搜索并管理笔记与知识库。
执行 Git 操作(提交、分支、合并、变基、冲突解决与恢复)时强制套用安全规则。
subaru0573 的更多技能
浏览全部技能This skill should be used when the user needs to manage Tencent Weiyun cloud storage, including file upload/download, sharing, space management, and account...
Data analysis and visualization. Query databases, generate reports, automate spreadsheets, and turn raw data into clear, actionable insights. Use when (1) yo...
Read and send email via IMAP/SMTP. Check for new/unread messages, fetch content, search mailboxes, mark as read/unread, and send emails with attachments. Sup...
Capture, inspect, and compare screenshots of screens, windows, regions, web pages, simulators, and CI runs with the right tool, wait strategy, viewport, and...
Create, inspect, and edit Microsoft Word documents and DOCX files with reliable styles, numbering, tracked changes, tables, sections, and compatibility check...
Analyze stocks and cryptocurrencies using Yahoo Finance data. Supports portfolio management, watchlists with alerts, dividend analysis, 8-dimension stock sco...