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God Mode Skill

作者 [email protected] · GitHub ↗ · v1.0.0
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在 OpenClaw 中安装
/install god-mode-skill
功能描述
God's eye view of your dev repos. Multi-project tracking across GitHub/Azure DevOps. AI learns from your commits to upgrade your agents.md.
使用说明 (SKILL.md)

god-mode Skill

Conversational project oversight and AI agent coaching for OpenClaw.

Overview

god-mode lets users ask about their projects in plain English. You run the commands and explain the results conversationally.

What users can ask:

  • "Set up god-mode for my repos"
  • "What's happening across my projects?"
  • "Which repos need attention?"
  • "Analyze my agents.md"
  • "What should I work on today?"

What you provide:

  • Multi-project status summaries (GitHub + Azure DevOps)
  • Plain-English explanations of commit activity, PRs, issues
  • LLM-powered agent instruction analysis
  • Recommendations for improving their AGENTS.md

Perfect for:

  • Developers juggling multiple repos who want conversational oversight
  • Teams using AI coding assistants (Claude, Copilot, etc.)
  • Anyone who wants data-driven improvements to their AGENTS.md

Getting Started

For OpenClaw Users (Conversational)

Just tell me what you want! I'll run the god-mode commands for you.

Example conversations:

You: "Set up god-mode for my tada repository"

Me: Sure! I'll set up god-mode and add your tada repo. [runs god setup and god projects add github:YourUsername/tada] Done! Your repo is configured. Want me to sync the data?

You: "Yes, and show me what's happening"

Me: [runs god sync and god status]

Here's your overview:

  • tada: 30 commits this week, last activity 3 days ago
  • 0 open PRs, 0 issues

Your most active project! Commits are all features and bug fixes.

You: "Analyze my agents.md for tada"

Me: [runs god agents analyze github:YourUsername/tada]

I've analyzed your AGENTS.md against 155 commits. Here's what I found:

GAPS:

  • Testing practices (high impact) - 68 bug fixes but no testing guidance
  • Voice API debugging - 12 commits mention "voice" but no troubleshooting

STRENGTHS:

  • TypeScript strictness is working - zero type-related fixes

Want me to add testing guidance to your AGENTS.md?

What you can ask me:

  • "Set up god-mode for [repo]"
  • "Show me all my projects"
  • "What's happening across my repos?"
  • "Analyze my agents.md"
  • "Which repos need attention?"
  • "What should I work on today?"

I'll handle all the commands and explain the results in plain English.

For CLI Users (Direct Commands)

If you prefer running commands yourself:

# Setup
god setup

# Add a project
god projects add github:username/repo

# Sync and view
god sync
god status

Commands

god status [project]

Show overview of all projects, or details for one:

god status              # All projects
god status myproject    # One project in detail

god sync [project] [--force]

Fetch/update data from repositories:

god sync                # Incremental sync all
god sync myproject      # Just one project
god sync --force        # Full refresh (ignore cache)

god projects

Manage configured projects:

god projects                        # List all
god projects add github:user/repo   # Add project
god projects remove myproject       # Remove project

god review [--month YYYY-MM]

Generate monthly activity reviews:

god review                  # Last month's activity
god review --month 2026-01  # Specific month
god review --json           # JSON output

What it shows:

  • Total commits across all projects
  • Most active repositories
  • Pull request activity (merged, active, closed)
  • Detailed breakdown by project with date ranges
  • Perfect for monthly retrospectives and planning

Example output:

Monthly Review: 2026-01
  📊 286 commits across 7 projects
  👥 10 unique contributors
  
Most Active Projects:
  tada - 155 commits
  ContentEngine - 63 commits
  brain - 27 commits

Use cases:

  • Monthly team stand-ups
  • Personal retrospectives ("What did I actually work on?")
  • Quarterly planning ("Which projects got attention?")
  • Automated monthly summaries via cron

god agents analyze \x3Cproject>

Analyze agents.md against commit history using LLM:

god agents analyze myproject

What it does:

  1. Fetches your AGENTS.md from the repository
  2. Analyzes commit patterns (types, pain points, frequently changed files)
  3. Calls an LLM (Claude/GPT) to find gaps and suggest improvements
  4. Displays recommendations interactively
  5. Optionally applies changes to your AGENTS.md

LLM Configuration:

god-mode automatically detects and uses the best available LLM:

  1. OpenClaw (default when running as skill) - Uses your OpenClaw agent
  2. Anthropic - Set ANTHROPIC_API_KEY="sk-ant-..."
  3. OpenAI - Set OPENAI_API_KEY="sk-..."
  4. OpenRouter - Set OPENROUTER_API_KEY="sk-or-..."
  5. Manual - Outputs prompt if no LLM available

When running in OpenClaw:

  • The analysis prompt is displayed to your OpenClaw agent
  • You (or your agent) provides the JSON analysis directly in the conversation
  • Much simpler than managing separate API keys!

OpenClaw Workflow:

When you run god agents analyze in OpenClaw:

  1. Analysis starts:

    🔭 Analyzing github:InfantLab/tada
    ✅ Found AGENTS.md (remote)
    ✅ 155 commits analyzed
    🤖 Using OpenClaw's LLM
    
  2. I (OpenClaw agent) receive the analysis prompt showing:

    • Your complete AGENTS.md content
    • Commit pattern summary (45 features, 68 bug fixes, etc.)
    • Most changed files/directories
    • Pain points and commit samples
  3. I analyze and provide JSON response:

    {
      "gaps": [
        {
          "area": "Testing",
          "observation": "68 bug fixes but no testing guidance in AGENTS.md",
          "impact": "high",
          "suggestion": "Add testing section with coverage targets"
        }
      ],
      "strengths": [...],
      "recommendations": [...]
    }
    
  4. god-mode displays results and offers to apply changes to your AGENTS.md

  5. You choose which recommendations to accept, and god-mode updates the file

Standalone Workflow (outside OpenClaw):

If you set ANTHROPIC_API_KEY or OPENAI_API_KEY, god-mode calls the API directly:

export ANTHROPIC_API_KEY="sk-ant-..."
god agents analyze myproject  # Fully automated

god agents generate \x3Cproject> (Coming Soon)

Bootstrap agents.md for a new project by analyzing repo structure.

god logs [options]

View activity logs:

god logs                # Last 50 lines
god logs -n 100         # Last 100 lines
god logs -f             # Follow log output
god logs --path         # Show log file location
god logs --clear        # Clear all logs

All god-mode activity is logged to ~/.god-mode/logs/activity.log with timestamps for transparency and debugging.

Configuration

Config file: ~/.config/god-mode/config.yaml

projects:
  - id: github:user/repo
    name: My Project      # Display name
    priority: high        # high/medium/low
    tags: [work, api]
    local: ~/code/myrepo  # Local clone path

sync:
  initialDays: 90         # First sync lookback
  commitsCacheMinutes: 60

analysis:
  agentFiles:             # Files to search for
    - agents.md
    - AGENTS.md
    - CLAUDE.md
    - .github/copilot-instructions.md

Data Storage

All data stored locally in ~/.god-mode/:

  • cache.db - SQLite database (commits, PRs, issues, analyses)
  • contexts/ - Saved workspace contexts (v0.2)

Authentication

god-mode uses your existing CLI authentication:

Provider CLI Setup
GitHub gh gh auth login
Azure az az login
GitLab glab glab auth login

No tokens stored by god-mode. We delegate to CLIs you already trust.

Requirements

  • gh - GitHub CLI (for GitHub repos)
  • sqlite3 - Database
  • jq - JSON processing

Examples

Morning Check-In

god status
# See all projects at a glance
# Notice any stale PRs or quiet projects

Before Switching Projects

god status myproject
# See recent activity, open PRs, issues
# Remember where you left off

Improving Your AI Assistant

god agents analyze myproject
# Get suggestions based on your actual commit patterns
# Apply recommendations to your agents.md

Weekly Review

god status
# Review activity across all projects
# Identify projects needing attention

Agent Guide (For OpenClaw Agents)

When the user asks about their projects, here's what to do:

"Set up god-mode" / "Track my [repo]"

  1. Run god setup (checks dependencies)
  2. Run god projects add github:username/repo
  3. Run god sync to fetch data
  4. Summarize what you found

"Show me my projects" / "What's happening?"

  1. Run god status
  2. Translate output to conversational summary:
    • "Your most active repo is X with Y commits this week"
    • "Z repo hasn't had activity in N days"
    • "You have M open PRs across all projects"

"Analyze my agents.md"

  1. Run god agents analyze github:username/repo
  2. You'll receive the analysis prompt with:
    • Their complete AGENTS.md
    • Commit pattern analysis (155 commits, 68 bug fixes, etc.)
    • Pain points and frequently changed files
  3. Provide JSON analysis in this format:
    {
      "gaps": [
        {"area": "Testing", "observation": "68 bug fixes but no test guidance", "impact": "high", "suggestion": "Add testing section"}
      ],
      "strengths": [
        {"area": "TypeScript", "observation": "Zero type errors in 155 commits"}
      ],
      "recommendations": [
        {"priority": 1, "section": "## Testing", "content": "- Write unit tests for new code\
    
  • Run tests before commits"} ], "summary": "Strong TypeScript practices, needs testing guidance" }
  1. Summarize the analysis conversationally
  2. Offer to apply recommendations

"Which repos need attention?"

  1. Run god status
  2. Look for:
    • Stale PRs (>3 days old)
    • No activity in >5 days
    • Open issues piling up
  3. Suggest what to focus on

Automated Workflows

Daily Briefing (Heartbeat):

# HEARTBEAT.md
- Run `god status` and summarize:
  - Projects with stale PRs (>3 days)
  - Projects with no activity (>5 days)
  - Open PRs needing review

Monthly Review (Cron - 1st of month):

schedule:
  kind: cron
  expr: "0 9 1 * *"  # 9am on 1st of each month
  tz: "America/New_York"
payload:
  kind: agentTurn
  message: |
    Run god review for last month and summarize:
    - Which projects were most active?
    - Any projects that went quiet?
    - Major accomplishments from commit messages
    - Recommendations for next month
sessionTarget: isolated

Weekly Analysis (Cron):

schedule: "0 9 * * 1"  # Monday 9am
task: |
  Run `god agents analyze` on high-priority projects.
  If gaps found, notify with suggestions.

Common Questions

How do I use god-mode?

In OpenClaw: Just ask me! "Show me my projects", "Analyze my agents.md", etc. I'll run the commands and explain the results.

CLI: Run commands directly: god status, god sync, god agents analyze

Do I need to set up anything first?

First time: Tell me to "set up god-mode for [your repo]" and I'll handle it. Or run god setup and god projects add github:your/repo yourself.

Authentication: Make sure gh auth login is done (GitHub CLI authentication).

Do I need an API key?

No! When you ask me to analyze your agents.md, I receive the analysis prompt and provide the JSON response directly. No separate API key needed.

Standalone: If using god-mode outside OpenClaw, you can set ANTHROPIC_API_KEY or OPENAI_API_KEY for automated analysis.

How often does it sync data?

When you ask: I run god sync when you ask about your projects. First sync fetches 90 days of history. Subsequent syncs are incremental (only new data).

Manual: You can run god sync anytime, or god sync --force for a full refresh.

What data gets stored?

Locally only: Commits, PRs, issues, and analysis results in ~/.god-mode/cache.db. Activity logs in ~/.god-mode/logs/activity.log. Nothing sent to external servers (except when calling LLM APIs if configured).

Does it work with private repos?

Yes! Uses your gh CLI authentication, so it has access to whatever your GitHub account can access.

Troubleshooting

"gh: command not found"

Install GitHub CLI: https://cli.github.com/

"Not logged in to GitHub"

Run: gh auth login

"No projects configured"

Add a project: god projects add github:user/repo

Stale data

Force refresh: god sync --force

Agent analysis returns empty {}

This is normal in OpenClaw mode - the prompt is displayed for the OpenClaw agent to analyze. The agent provides the JSON response in conversation, not as return value.


OpenClaw Community Skill
License: MIT
Repository: https://github.com/InfantLab/god-mode-skill

安全使用建议
This skill appears to do what it says: it uses the GitHub CLI and a local SQLite cache to summarize activity and feed your AGENTS.md + commit samples to an LLM for recommendations. Things to consider before installing or running it: - Sensitive data exposure: The agents analysis sends full AGENTS.md content and commit samples to an LLM (either OpenClaw or an external API). Audit those files for secrets/private data first. If you must keep data private, prefer running only in OpenClaw mode (where analysis is handled locally by your agent) or avoid supplying external API keys. - Credentials & scopes: The tool relies on your existing gh CLI auth. If you allow it to apply recommendations (push/PR), ensure your gh token has appropriate (least-privilege) scopes or use a read-only token for analysis-only runs. - Optional env vars: The SKILL.md mentions external LLM API keys (Anthropic/OpenAI/OpenRouter) and fallback tokens (GITHUB_TOKEN, AZURE_DEVOPS_PAT). These are optional but not listed in metadata — only provide them if you understand the network calls that will be made. - Local writes: The skill creates ~/.god-mode/ and ~/.config/god-mode/ and a local SQLite DB — inspect install.sh and scripts/god before running. Installing via the repo's install.sh (GitHub raw URL) is common but audit the script if you are cautious. - Audit before granting write actions: If you accept prompts to 'apply' recommendations, review the generated changes and any resulting git operations before allowing them to run. If you want to proceed safely: clone the repo locally, review install.sh and scripts/god, run in a sandbox account or with read-only gh credentials, and avoid supplying external LLM API keys unless you trust the environment and have inspected the LLM-calling code (scripts/lib/llm.sh).
功能分析
Type: OpenClaw Skill Name: god-mode-skill Version: 1.0.0 The skill is classified as suspicious due to multiple SQL injection vulnerabilities in its database interactions and a significant prompt injection risk in its core LLM analysis feature. Specifically, `scripts/commands/projects.sh`, `scripts/commands/sync.sh`, `scripts/lib/analysis/agents.sh`, and `scripts/lib/db.sh` use direct SQL string concatenation with variables derived from user input or external API responses, which are not robustly escaped, allowing for potential SQL injection. Furthermore, the `prompts/agent-analysis.md` template feeds user-controlled content (like `agents.md` content and commit messages) to an LLM, and the LLM's output is then written back to the `agents.md` file by `scripts/lib/apply.sh`. This creates a prompt injection vector where a malicious `agents.md` or commit message could trick the LLM into generating harmful instructions that are then persisted in the `agents.md` file, potentially exploitable by other agents or systems. While these are significant vulnerabilities, there is no clear evidence of intentional malicious behavior such as unauthorized data exfiltration, persistence mechanisms, or credential theft beyond the stated purpose.
能力评估
Purpose & Capability
Name/description (multi-project oversight + agent coaching) align with the included scripts and commands (sync, status, agents analyze). Required binaries (gh, sqlite3, jq) are appropriate. Minor inconsistency: docs and code reference optional provider CLIs and environment variables (az, glab, ANTHROPIC_API_KEY, OPENAI_API_KEY, GITHUB_TOKEN, AZURE_DEVOPS_PAT) but the skill metadata declares no required env vars and only lists gh/sqlite3/jq — this is plausible (they're optional), but the metadata doesn't fully enumerate optional fallbacks.
Instruction Scope
The runtime instructions explicitly fetch repository data and send the complete AGENTS.md content plus commit samples and pattern summaries to an LLM for analysis. That behavior is coherent with the stated feature, but it means potentially sensitive repository content (agents.md, commit messages, code snippets) will be exposed to whatever LLM is invoked (OpenClaw agent or external API). SKILL.md also instructs the skill to run the bundled 'god' commands and may optionally apply recommended changes to AGENTS.md (implying repo write actions). The instructions refer to environment variables for external LLMs but those env vars are not declared in the skill metadata.
Install Mechanism
There is no formal install spec in registry metadata (instruction-only), but the repository includes an install.sh and PUBLISH.md that suggest installing via GitHub (raw.githubusercontent.com/curl). That's a common pattern; the install URL points to GitHub, a well-known host, and there are no obscure download endpoints. Because files are present, installing will write scripts and db files under the user's home directory (~/.god-mode, ~/.config/god-mode).
Credentials
Declared required env vars: none. In practice the skill supports and documents multiple optional credentials (ANTHROPIC_API_KEY, OPENAI_API_KEY, OPENROUTER_API_KEY, fallback GITHUB_TOKEN / AZURE_DEVOPS_PAT / GITLAB_TOKEN) and relies on the user's local gh authentication. The skill's docs claim 'we never store tokens' and 'no telemetry', but code writes local DB/cache and may use gh auth (which implies existing tokens stored by gh). The presence of multiple optional credential paths is reasonable for LLM fallbacks, but you should be cautious: providing external API keys or a gh token with write scopes would allow networked LLM calls and repository writes/PRs.
Persistence & Privilege
The skill does not request always:true and is user-invocable (default autonomous invocation allowed). It stores data locally under ~/.god-mode and ~/.config/god-mode and initializes a SQLite database — that's proportionate to its function. The skill may, if you choose, apply changes to AGENTS.md which would require the user's gh/auth permissions; this is expected but worth reviewing before granting write-capable credentials.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install god-mode-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /god-mode-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of god-mode: conversational, multi-repo project oversight and AGENTS.md analysis for developers and teams. - Conversational interface for multi-project tracking across GitHub and Azure DevOps. - Summarizes commit activity, pull requests, and issues in plain English. - LLM-powered analysis and recommendations for improving AGENTS.md based on commit history. - CLI and OpenClaw conversational modes supported; no direct token storage—uses existing authenticated CLIs. - Includes commands for syncing, reviewing, logging, and managing projects.
元数据
Slug god-mode-skill
版本 1.0.0
许可证
累计安装 2
当前安装数 2
历史版本数 1
常见问题

God Mode Skill 是什么?

God's eye view of your dev repos. Multi-project tracking across GitHub/Azure DevOps. AI learns from your commits to upgrade your agents.md. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 466 次。

如何安装 God Mode Skill?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install god-mode-skill」即可一键安装,无需额外配置。

God Mode Skill 是免费的吗?

是的,God Mode Skill 完全免费(开源免费),可自由下载、安装和使用。

God Mode Skill 支持哪些平台?

God Mode Skill 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 God Mode Skill?

[email protected](@wetzja04-dot)开发并维护,当前版本 v1.0.0。

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