Geofeed-Tuner
Geofeed-Tuner是一款code方向的AI技能,核心价值是>,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
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mkdir -p ./skills/geofeed-tuner && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/geofeed-tuner/SKILL.md -o ./skills/geofeed-tuner/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Geofeed Tuner – Create Better IP Geolocation Feeds
This skill helps you create and improve IP geolocation feeds in CSV format by:
- Ensuring your CSV is well-formed and consistent
- Checking alignment with [RFC 8805](references/rfc8805.txt) (the industry standard)
- Applying **opinionated best practices** learned from real-world deployments
- Suggesting improvements for accuracy, completeness, and privacy
When to Use This Skill
- Use this skill when a user asks for help **creating, improving, or publishing** an IP geolocation feed file in CSV format.
- Use it to **tune and troubleshoot CSV geolocation feeds** — catching errors, suggesting improvements, and ensuring real-world usability beyond RFC compliance.
- **Intended audience:**
- Network operators, administrators, and engineers responsible for publicly routable IP address space
- Organizations such as ISPs, mobile carriers, cloud providers, hosting and colocation companies, Internet Exchange operators, and satellite internet providers
- **Do not use** this skill for private or internal IP address management; it applies **only to publicly routable IP addresses**.
Prerequisites
- **Python 3** is required.
Directory Structure and File Management
This skill uses a clear separation between **distribution files** (read-only) and **working files** (generated at runtime).
Read-Only Directories (Do Not Modify)
The following directories contain static distribution assets. **Do not create, modify, or delete files in these directories:**
| Directory | Purpose |
|----------------|------------------------------------------------------------|
| `assets/` | Static data files (ISO codes, examples) |
| `references/` | RFC specifications and code snippets for reference |
| `scripts/` | Executable code and HTML template files for reports |
Working Directories (Generated Content)
All generated, temporary, and output files go in these directories:
| Directory | Purpose |
|-----------------|------------------------------------------------------|
| `run/` | Working directory for all agent-generated content |
| `run/data/` | Downloaded CSV files from remote URLs |
| `run/report/` | Generated HTML tuning reports |
File Management Rules
1. **Never write to `assets/`, `references/`, or `scripts/`** — these are part of the skill distribution and must remain unchanged.
2. **All downloaded input files** (from remote URLs) must be saved to `./run/data/`.
3. **All generated HTML reports** must be saved to `./run/report/`.
4. **All generated Python scripts** must be saved to `./run/`.
5. The `run/` directory may be cleared between sessions; do not store permanent data there.
6. **Working directory for execution:** All generated scripts in `./run/` must be executed with the **skill root directory** (the directory containing `SKILL.md`) as the current working directory, so that relative paths like `assets/iso3166-1.json` and `./run/data/report-data.json` resolve correctly. Do not `cd` into `./run/` before running scripts.
Processing Pipeline: Sequential Phase Execution
All phases must be executed **in order**, from Phase 1 through Phase 6. Each phase depends on the successful completion of the previous phase. For example, **structure checks** must complete before **quality analysis** can run.
The phases are summarized below. The agent must follow the detailed steps outlined further in each phase section.
| Phase | Name | Description |
|-------|----------------------------|-----------------------------------------------------------------------------------|
| 1 | Understand the Standard | Review the key requirements of RFC 8805 for self-published IP geolocatio
🎯 Best For
- Claude users
- GitHub Copilot users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Geofeed-Tuner to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is Geofeed-Tuner compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Geofeed-Tuner?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Geofeed-Tuner?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/geofeed-tuner/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.