auto-doc

An automatic documentation process that updates project guides and a module registry after code or API changes.

In plain words
What is it for?
Use it after adding features, changing APIs or modules, passing tests, or when documentation updates are explicitly requested.
Why use it?
It reduces the chance that documentation, integration instructions, or the change log will fall behind the code.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/yxhpy/openuser/auto-doc
Any agent
npx skills add yxhpy/openuser --skill auto-doc
Clone the repo
git clone --depth 1 https://github.com/yxhpy/openuser

Made for: Claude Code, Codex.

Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,693 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00031 $0.01693
Opus 5 $0.00015 $0.00847
Sonnet 5 $0.00006 $0.00339
Haiku 4.5 $0.00003 $0.00169

Measured 2d ago against content hash 0860c899ac2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

auto-doc scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

response = requests.post( "http://localhost:8000/api/v1/digital-human/create",

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.post(
.claude/skills/auto-doc/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auto Documentation Skill

This skill automatically updates documentation and module registry after code changes.

Trigger Conditions

This skill is triggered when:

  • New feature is implemented
  • API endpoints are added/modified
  • Module structure changes
  • Tests pass successfully
  • User explicitly requests documentation update

Behavior

When triggered, this skill will:

  1. Detect Changes - Identify what was modified
  2. Update Module Registry - Add new modules to docs/modules/REGISTRY.md
  3. Update API Docs - Regenerate API documentation
  4. Update Integration Docs - Update integration guides if needed
  5. Update CHANGELOG - Record changes in CHANGELOG.md
  6. Verify Links - Check all documentation links are valid
  7. Record in Memory - Update project memory with changes

Documentation Structure

docs/
├── INDEX.md                      # Main documentation index
├── modules/
│   └── REGISTRY.md              # Module registry (prevent duplication)
├── api/
│   ├── INDEX.md                 # API overview
│   ├── digital-human.md         # Digital human endpoints
│   ├── plugins.md               # Plugin endpoints
│   ├── agents.md                # Agent endpoints
│   └── scheduler.md             # Scheduler endpoints
├── integrations/
│   ├── FEISHU.md               # Feishu integration guide
│   ├── WECHAT.md               # WeChat Work integration guide
│   └── WEB.md                  # Web interface guide
└── troubleshooting/
    ├── KNOWN_ISSUES.md         # Known issues and solutions
    └── FAQ.md                  # Frequently asked questions

Module Registry Format

docs/modules/REGISTRY.md tracks all implemented modules to prevent duplication:

# Module Registry

## Core Modules

### Plugin Manager
- **Path**: `src/core/plugin_manager.py`
- **Purpose**: Hot-reload plugin system
- **Status**: ✅ Implemented
- **Test Coverage**: 100%
- **Dependencies**: None
- **API**: `PluginManager.load_plugin()`, `PluginManager.reload_plugin()`

### Agent Manager
- **Path**: `src/core/agent_manager.py`
- **Purpose**: AI agent lifecycle management
- **Status**: ✅ Implemented
- **Test Coverage**: 100%
- **Dependencies**: Plugin Manager
- **API**: `AgentManager.create_agent()`, `AgentManager.update_agent()`

## Plugins

### Image Processor
- **Path**: `src/plugins/image_processor.py`
- **Purpose**: Image preprocessing and enhancement
- **Status**: ✅ Implemented
- **Test Coverage**: 100%
- **Dependencies**: PIL, OpenCV
- **API**: `ImageProcessor.process()`

## Integrations

### Feishu Integration
- **Path**: `src/integrations/feishu/`
- **Purpose**: Feishu bot integration
- **Status**: 🚧 In Progress
- **Test Coverage**: 80%
- **Dependencies**: httpx
- **API**: `FeishuBot.send_message()`, `FeishuBot.handle_webhook()`

Read the full file on GitHub · 296 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 296 lines · 31 tokens per session scan B 0860c899ac2c

Subscribe to this mod's changes

auto-doc is a skill published in the GitHub repository yxhpy/openuser (2 stars, last pushed 7mo ago), licensed MIT. It adds 31 tokens to every session and 1,693 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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