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/suitable-adventures/suitable-loop/health-checkgit clone --depth 1 https://github.com/suitable-adventures/suitable-loopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/suitable-adventures/suitable-loop/health-check)<a href="https://agentmods.dev/commands/suitable-adventures/suitable-loop/health-check"><img src="https://agentmods.dev/badge/commands/suitable-adventures/suitable-loop/health-check.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00227 |
| Opus 5 | $0.00000 | $0.00113 |
| Sonnet 5 | $0.00000 | $0.00045 |
| Haiku 4.5 | $0.00000 | $0.00023 |
Grade A, and why
health-check 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.
What it actually says
Run a full codebase health check using Suitable Loop.
Steps:
- Use
reindexon the current project to ensure data is fresh - Use
codebase_summaryfor overall stats - Use
complexity_report(top 15) to find overly complex code - Use
hotspot_reporton this repo (last 100 commits) to find high-risk areas - Use
blast_radiuson the top 5 most-depended-upon files - Use
analyze_recent_changes(last 20 commits) to check recent risk trends
Produce a health report with these sections:
Codebase overview — size, structure, key metrics
Complexity hotspots — functions above complexity 15, with recommendations to simplify
Dependency risks — files with the largest blast radius, coupling concerns
Change hotspots — files that change too often relative to how many things depend on them
Recent risk trend — are recent commits getting riskier or safer?
Recommendations — top 3 actionable items to improve codebase health
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 · 24 lines · 0 tokens per session scan A 52ebbeb8914b
health-check is a command published in the GitHub repository suitable-adventures/suitable-loop (0 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 227 tokens. 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 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.