MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

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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Last verified on: 2026-05-30
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. 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. 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. 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. 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.

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