geofeed-tuner
Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Intended user audience is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, or geofeed authoring best practices. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to pu
Profile →npx skills add github/awesome-copilot --skill geofeed-tuner --agent copilot
Same command for any agent — swap --agent for claude-code, codex, cursor.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The geofeed-tuner skill helps create and improve IP geolocation feeds in CSV format by ensuring the CSV is well-formed, aligned with RFC 8805, and augmented with opinionated best-practices to improve accuracy, completeness, and privacy. It targets operators and service providers who publish or tune publicly routable IP geolocation data.
How it works
- Follows a six-phase processing pipeline executed in order: Understand the Standard, Gather Input, Checks & Suggestions, Tuning Data Lookup, Generate Tuning Report, and Final Review. Before each phase, it generates a live TODO checklist presented at the start of the phase.
- Phase 1 (Understand the Standard): uses RFC 8805 key facts as the working reference to enforce requirements such as CSV columns, UTF-8 encoding, proper CIDR notation, and do-not-geolocate signaling. (Phase-specific details are laid out in the plan and references.)
- Phase 2 (Gather Input): accepts input as local text, a local CSV file, or a remote URL; downloads remote inputs to ./run/data/ and decodes with UTF-8 or fallbacks; errors on unrecoverable encodings.
- Phase 3 (Checks & Suggestions): generates a script for this phase and stores a JSON report at ./run/data/report-data.json; uses a fixed, immutable schema for the report with fields like InputFile, Timestamp, TotalEntries, Errors, Warnings, OK, and per-entry details including IPPrefix, CountryCode, RegionCode, City, and Messages. Messages contain IDs, Types, Text, and Checked flags; DoNotGeolocate and Tunable flags are computed from the data.
- Phase 4 (Tuning Data Lookup): retrieves tuning data via Fastah MCP tooling to improve geolocation accuracy.
- Phase 5 (Generate Tuning Report): produces an HTML report summarizing analyses and recommendations and saves to ./run/report/.
- Phase 6 (Final Review): confirms consistency and completeness of the report data.
When to use it
Use this skill when creating, improving, or publishing a CSV IP geolocation feed for publicly routable IPs, needing quality checks beyond RFC 8805 compliance, and when you want optimization suggestions for accuracy, completeness, and privacy. Intended audience includes network operators, ISPs, mobile carriers, cloud providers, hosting companies, IXPs, and satellite providers.
What it can touch
- Requires Python 3.
- Interacts with working directories: ./run/ (for scripts), ./run/data/ (for downloaded inputs and report data), and ./run/report/ (for HTML reports).
- Uses assets/ references/ and scripts/ as read-only resources that must not be modified.
Caveats
- Do not use for private or internal IP address management; applies only to publicly routable IP addresses.
- License: Apache-2.0 for the skill, with the author listed as Sid Mathur.
- The processing relies on a fixed JSON schema for Phase 3 output, which is immutable during that phase and later extended in Phase 4 with TunedEntry data.
# 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 St
- When to Use This Skill
- Prerequisites
- Directory Structure and File Management
- Read-Only Directories (Do Not Modify)
- Working Directories (Generated Content)
- File Management Rules
- Processing Pipeline: Sequential Phase Execution
- Execution Plan Rules
- Phase 1: Understand the Standard
- Phase 2: Gather Input
- Phase 3: Checks & Suggestions
- Phase 4: Tuning Data Lookup
- Phase 6: Final Review
What does the geofeed-tuner skill do?
Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Intended user audience is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, or geofeed authoring best practices. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to pu
How do I install it?
Run `npx skills add github/awesome-copilot --skill geofeed-tuner --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.