Review
Football data analytics toolkit for Claude Code. Covers Opta, StatsBomb, Wyscout, SportMonks, and free sources.
npx -y skills add withqwerty/nutmeg --skill reviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
What its author says it does
Copied from the file, not written here
Review football data code and visualisations for correctness. Use after building a chart, data pipeline, or analysis. Dispatches specialised reviewers for data correctness, chart conventions, visual inspection, and interactive edge cases.
SKILL.md
4.1 KB, as published. Nobody here has run it
Review
Dispatch specialised reviewers to check football data code and visualisations for correctness, convention compliance, and edge cases.
Accuracy
Read and follow docs/accuracy-guardrail.md before answering any question about provider-specific facts.
First: check profile
Read .nutmeg.user.md. If it doesn't exist, tell the user to run /nutmeg first.
Determine scope
Look at what the user wants reviewed. Read the relevant files. Then decide which reviewers to dispatch:
| Signal | Dispatch |
|---|---|
| Code processes football data (fetching, filtering, transforming, computing metrics) | data-reviewer agent |
| Code renders a chart or visualisation | chart-reviewer agent (Mode 1: Code Review) |
| User provides a URL or says "check how it looks" | chart-reviewer agent (Mode 2: Visual Inspection) |
| Chart has filters, tooltips, state, or dynamic data | chart-reviewer agent (Mode 3: Interactive Edge Cases) |
Code imports @withqwerty/campos-* (React + campos) | chart-reviewer agent (Mode 4: React + Campos) — pass skills/_shared/campos-bridge.md in context |
| Code does both data processing AND chart rendering | Both agents in parallel |
Always dispatch at least one. If unclear, dispatch both — redundant findings are better than missed issues.
Detection for Mode 4: grep the reviewed files for @withqwerty/campos- or from "@withqwerty/campos. Any match activates Mode 4 alongside Mode 1.
Dispatch
Spawn agents in parallel when dispatching multiple. Each agent receives:
- The file paths to review
- The user's profile (language, provider, experience level)
- Which mode(s) to run (for chart-reviewer)
- Context: what the user said they built and what they're worried about
Data reviewer prompt template
Review the football data code in [FILE_PATHS].
The user is working with [PROVIDER] data in [LANGUAGE].
They built: [DESCRIPTION]
Their concern: [WHAT_THEY_SAID]
Follow the full review checklist in your agent prompt. Use search_docs to verify
provider-specific facts (coordinate systems, qualifier IDs, event types).
Chart reviewer prompt template
Review the chart code in [FILE_PATHS].
Mode(s): [Code Review / Visual Inspection / Interactive Edge Cases]
The user is building: [DESCRIPTION]
Their concern: [WHAT_THEY_SAID]
Stack: [LANGUAGE + LIBRARIES from profile]
[If visual inspection: URL or instructions to render]
Load skills/brainstorm/references/chart-canon.md for convention checking.
Synthesise findings
After both agents report back:
- Deduplicate — if both flag the same issue (e.g., wrong coordinate system), merge into one finding
- Sort by severity — Critical first, then Warning, then Info
- Group logically — Data issues, then Rendering issues, then Convention issues, then Edge cases
- Present concisely — table format with severity, location, issue, fix
When to suggest visual inspection
If the chart-reviewer's code review finds potential rendering issues but can't confirm without seeing the output, suggest:
"The code review found [N] potential rendering issues. Want me to visually inspect the chart? I'll need a URL or you can run it locally."
Don't require visual inspection — many users can't easily serve their chart locally. Code review alone catches most issues.
After review
If findings are found:
- Ask the user which ones to fix
- For Critical issues, offer to fix them directly
- For Warning/Info, explain the trade-off and let them decide
If no findings:
- Say so clearly. Don't invent issues to justify the review.
- Optionally mention what was checked so the user knows the review was thorough.