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/check-codegit 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 | $0.00007 | $0.00194 |
| Opus 5 | $0.00003 | $0.00097 |
| Sonnet 5 | $0.00001 | $0.00039 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
check-code 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 yesterday.
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.
What it actually says
Check Code
Look at the code in the current directory or the path provided by the user.
Run these checks:
- Run
ruff check .to find linting issues - Run
ruff format --check .to check formatting - Run
mypy . --ignore-missing-importsfor type checking - Run
pytest --cov -qto check test coverage
For each check, report:
- What passed
- What failed
- How to fix the failures
If all checks pass, tell the user the code looks good.
If there are failures, prioritize them:
- Security issues first
- Type errors second
- Lint issues third
- Formatting last
Also check if functions are too long (over 50 lines) and if there's code duplication.
At the end, give an overall verdict: READY or NEEDS WORK.
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.
- yesterday First seen · 31 lines · 7 tokens per session scan A 2af096cb0abc
check-code is a command published in the GitHub repository Benkapner/claude-code-basecamp (16 stars, last pushed 12d ago), licensed MIT. It adds 7 tokens to every session and 194 once invoked, about $0.0000 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.
review
Use when reviewing spec-forge generated documents for quality, completeness, and consistency — auto-fixes issues if found.
analyze
Use when analyzing a document collection to map themes, find conflicts, gaps, and redundancies — generates landscape analysis report.
audit
Use when auditing existing project docs for quality, completeness, and code alignment — generates findings report with fix recommendations.
test-cases
Use when writing test cases, generating tests, supplementing test coverage, or improving test completeness — auto-scans project, designs multi-dimensional test cases with coverage matrix.