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.
npx agentmods add commands/benkapner/claude-code-basecamp/test-coveragegit clone --depth 1 https://github.com/Benkapner/claude-code-basecampWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00019 | $0.01131 |
| Opus 5 | $0.00010 | $0.00566 |
| Sonnet 5 | $0.00004 | $0.00226 |
| Haiku 4.5 | $0.00002 | $0.00113 |
Grade A, and why
test-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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Coverage Command
Analyze test coverage, identify gaps, and generate missing tests.
Instructions
Step 0: Detect Test Runner and Coverage Target
Before running anything, detect the project's test runner and coverage target from config:
# Check for test runner config
cat pyproject.toml 2>/dev/null | grep -A5 'tool.pytest\|tool.coverage\|tool.unittest'
cat setup.cfg 2>/dev/null | grep -A5 'tool:pytest\|coverage'
cat pytest.ini 2>/dev/null
cat package.json 2>/dev/null | grep -E '"test"|"jest"|"mocha"|"vitest"'
- Test runner: use whatever the project configures (pytest, unittest, jest, vitest, etc.). Fall back to pytest only if nothing is configured and
pyproject.tomlexists. - Coverage target: read from
pyproject.toml([tool.coverage.report]→fail_under),setup.cfg, or.coveragerc. Fall back to 80% only if no target is configured.
If no test runner is detected, ask the user: "couldn't detect the test runner — what does this project use?"
Step 1: Run Coverage
Use the detected test runner. For pytest:
pytest --cov --cov-report=term-missing -q
Step 2: Analyze Coverage Report
- Parse the coverage output
- List files below the coverage target, sorted worst-first
- For each under-covered file, identify:
- Untested functions or methods
- Missing branch coverage (if/else, try/except, early returns)
- Dead code that inflates the denominator
If pytest/coverage is not available, perform static analysis instead:
- List all source files and their corresponding test files
- Flag source files with NO test file
- For files with tests, list public functions/methods that have no test
- Estimate coverage percentage based on tested vs untested functions
Testing Priority Classification:
- HIGH: Core business logic, security-sensitive functions, public APIs, complex algorithms, data pipeline stages
- MEDIUM: Utility functions, configuration loading, error handling paths
- LOW: Simple getters/setters, trivial wrappers, logging-only code
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.
- 3d ago First seen · 125 lines · 19 tokens per session scan A 3d2ae5b72b3e
test-coverage is a command published in the GitHub repository Benkapner/claude-code-basecamp (16 stars, last pushed 13d ago), licensed MIT. It adds 19 tokens to every session and 1,131 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
spec-forge
Use when generating software specifications — full chain (Idea→Decompose→Tech Design + Feature Specs) or individual documents.
propagate
Use after editing an upstream doc (PRD/SRS/tech-design/feature-spec) to propagate changes downstream and keep the entire doc chain consistent.
analyze
Use when analyzing a document collection to map themes, find conflicts, gaps, and redundancies — generates landscape analysis report.
review
Use when reviewing spec-forge generated documents for quality, completeness, and consistency — auto-fixes issues if found.
audit
Use when auditing existing project docs for quality, completeness, and code alignment — generates findings report with fix recommendations.
tech-design
Use when writing a tech design, architecture doc, RFC, or design document — follows Google Design Doc format.