ide-coverage

A tool that turns test-coverage reports into an HTML heatmap of the project’s files, with colors showing how much code tests exercise.

In plain words
What is it for?
Finding coverage reports, parsing line-coverage data, creating a file-tree heatmap, and opening the result in a browser.
Why use it?
It makes uneven or missing test coverage easier to spot than reading raw coverage files.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/oolab-labs/patchwork-os/ide-coverage
Any agent
npx skills add Oolab-labs/patchwork-os --skill ide-coverage
Clone the repo
git clone --depth 1 https://github.com/Oolab-labs/patchwork-os

Made for: Claude Code, Codex.

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 865 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00044 $0.00865
Opus 5 $0.00022 $0.00432
Sonnet 5 $0.00009 $0.00173
Haiku 4.5 $0.00004 $0.00086

Measured 3d ago against content hash 87835372e96d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ide-coverage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

94% identical to ide-coverage — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/ide-coverage/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generate a visual test coverage heatmap and open it in the browser.

This skill uses only built-in tools (Glob, Read, Write, Bash) and works in both IDE-connected and remote sessions.

Arguments

$ARGUMENTS can be:

  • A path to a specific coverage file (coverage/lcov.info, coverage/coverage-summary.json)
  • A directory to search within (coverage/)
  • Empty — auto-discover coverage files in the workspace

Steps

Phase 1 — Locate coverage data

  1. If $ARGUMENTS is a specific file path, use it directly.
  2. Otherwise use the Glob tool with patterns: **/lcov.info, **/coverage-summary.json, **/coverage-final.json (exclude node_modules).
  3. If multiple candidates found, prefer lcov.info > coverage-summary.json > coverage-final.json. If still ambiguous (multiple projects), list them and ask the user to specify.
  4. If no coverage file found: report "No coverage data found. Run npm test -- --coverage (or equivalent) first." and stop.

Phase 2 — Parse coverage

  1. Use the Read tool to read the located coverage file.
  2. Parse based on format:
    • lcov.info: iterate SF: (source file), LF: (lines found), LH: (lines hit) records → { file, totalLines, hitLines, pct }
    • coverage-summary.json (Istanbul/NYC): each key is a file path with { lines: { pct, total, covered } }
    • coverage-final.json: compute line pct from statement map s and statement map statementMap
  3. Build a list: { file: string (relative), pct: number, hitLines: number, totalLines: number }[]
  4. Group files by directory for the tree layout. Compute directory-level aggregate coverage.

Phase 3 — Generate and open HTML

  1. Construct a fully self-contained HTML document (no external URLs — must work from file://) containing:
    • A summary header: "Overall coverage: N% · M / K lines covered · P files"
    • Color scale: ≥80% = #22c55e (green), ≥50% = #eab308 (yellow), <50% = #ef4444 (red), no data = #94a3b8 (grey)
    • A collapsible directory tree using <details>/<summary> HTML elements (no JS needed for expand/collapse)
    • Each file as a row: [coverage bar] filename N% (hitLines/totalLines)
    • The coverage bar is an inline <span> with a CSS width: N% background — no canvas needed
    • Directory rows show aggregate coverage for the subtree
    • A legend at the top showing the color key
    • Clicking a file's name copies its relative path to clipboard (single JS event listener, ~10 lines)
    • Page title: "Coverage — "
  2. Write the HTML to coverage-<timestamp>.html in the workspace root using the Write tool.
  3. Open via Bash: open coverage-<timestamp>.html (macOS) or xdg-open (Linux). If openInBrowser MCP tool is available, use that instead.
  4. Report: "Opened coverage heatmap — overall N% line coverage across M files. Saved to: "

Read the full file on GitHub · 54 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 54 lines · 44 tokens per session scan A 87835372e96d

Subscribe to this mod's changes

ide-coverage is a skill published in the GitHub repository Oolab-labs/patchwork-os (30 stars, last pushed 3d ago), licensed MIT. It adds 44 tokens to every session and 865 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to ide-coverage, differing in 2 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens