A zero-dependency Python tool for generating AI-summarized daily reports and activity metrics for GitCode repositories.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install gitcode-repo-daily
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install gitcode-repo-daily using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is gitcode-repo-daily?
gitcode-repo-daily is a technical automation tool designed to streamline repository oversight by generating comprehensive daily reports. By utilizing Openclaw Skills, it fetches repository data, processes activity metrics, and produces AI-driven summaries of merged Pull Requests and hot issues. The tool is built to run on Python 3.7+ using only the standard library, ensuring maximum compatibility across Windows, macOS, and Linux environments without the need for external pip dependencies.
This skill bridges the gap between raw Git data and actionable insights, providing developers and managers with a clear view of daily progress. It automates the entire lifecycle from data retrieval via the GitCode API to local database storage and final Markdown rendering, making it a vital component for teams using Openclaw Skills for project management.
gitcode-repo-daily Use Cases
- Automatically generating daily stand-up reports for GitCode-based development teams.
- Monitoring repository health and activity levels across multiple projects without manual checking.
- Archiving AI-summarized project milestones in a local SQLite database for historical audit trails.
- Streamlining stakeholder communication by providing structured, easy-to-read Markdown operation reports through Openclaw Skills.
How gitcode-repo-daily Works
- The tool resolves the target date and repository list from user input or the local configuration file.
- It authenticates with GitCode using a secure token to fetch daily metrics, including PRs, issues, and commit data.
- Raw data is processed into a structured JSON report and saved to a temporary directory.
- The agent generates concise AI summaries for each repository based on the merged PR descriptions.
- The skill executes a rendering command to transform the data and summaries into a standardized Markdown report using a predefined template.
- Summaries and metrics are automatically persisted into a local database for future reference.
gitcode-repo-daily Setup
To use this skill within your environment, ensure you have Python 3.7+ installed and set up your authentication token:
# For Linux or macOS, add to your shell profile
export GITCODE_TOKEN="your_gitcode_token_here"
# For Windows, set the environment variable in System Properties or via PowerShell
$env:GITCODE_TOKEN="your_gitcode_token_here"
# Run the report generator for specific repositories
python scripts/generate_daily_report.py --repos "owner/repo1,owner/repo2"
gitcode-repo-daily Data Schema & Taxonomy
The skill organizes its operations through a clear file and metadata taxonomy to ensure reliability within Openclaw Skills workflows:
| File Path | Description | Format |
|---|---|---|
| config.json | Stores the default repository list and persistent settings. | JSON |
| temp_dir/report.json | Contains raw metrics and data fetched from GitCode. | JSON |
| temp_dir/summaries.json | Stores AI-generated repository and global summaries. | JSON |
| resources/report.db | Local SQLite database for persistent historical storage. | SQLite |
| resources/daily_report.md | The fixed template used for Markdown rendering. | Markdown |
gitcode-repo-daily Advanced Features
- Smart repository persistence: Any repository specified via CLI is automatically saved to the configuration for future use.
- Template-driven rendering: Ensures all reports follow a consistent organizational structure including emoji-coded headers and action items.
- Multi-platform environment variable resolution: Supports process-level, user-level, and system-level token detection on Windows.
- AI Summary Integration: Specifically designed to work with LLMs to condense complex git activities into one-sentence global summaries.
- Zero-dependency architecture: Operates entirely on Python standard libraries to avoid package conflicts in Openclaw Skills deployments.
SKILL.md
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