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/hanhuark/mechanical-engineering-research-skill/me-code-sanitygit clone --depth 1 https://github.com/hanhuark/mechanical-engineering-research-skillWrote 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/hanhuark/mechanical-engineering-research-skill/me-code-sanity)<a href="https://agentmods.dev/commands/hanhuark/mechanical-engineering-research-skill/me-code-sanity"><img src="https://agentmods.dev/badge/commands/hanhuark/mechanical-engineering-research-skill/me-code-sanity.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 5.1 | $0.00026 | $0.00254 |
| Opus 5 | $0.00013 | $0.00127 |
| Sonnet 5 | $0.00005 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
me-code-sanity 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 6d 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
Thermal-Fluid Code Sanity Review
Use mechanical-engineering-research for a fast preflight of code used for experiments, CFD post-processing, plotting, or AI/ML workflows. Escalate to me-code-review when architecture, refactoring, packaging, or release readiness is in scope.
Workflow:
- Identify the research question, input data, expected output, and baseline case.
- Check units, property sources, coordinate systems, time bases, sign conventions, and saved intermediate data.
- Check that raw data are preserved and processing stages are reproducible.
- Add sanity checks from conservation laws, correlations, analytical limits, known benchmark cases, or dimensional analysis.
- For AI/ML workflows, check train/validation/test separation across meaningful thermal-fluid conditions.
- Check that plots are traceable to data and that figure labels, uncertainty, and case metadata are publication-ready.
Expected output:
- code-risk findings ordered by severity
- missing physics or data checks
- reproducibility improvements
- lightweight tests or assertions
- plot and artifact traceability checklist
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.
- 6d ago First seen · 25 lines · 26 tokens per session scan A b35409ebcbc9
me-code-sanity is a command published in the GitHub repository hanhuark/mechanical-engineering-research-skill (16 stars, last pushed 8d ago), licensed MIT. It adds 26 tokens to every session and 254 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
refine-title
深度分析 Issue 或 PR 内容，并将其标题重构为 Conventional Commits 格式.
fit-analyze-codescan
分析 Code Scanning 告警并创建安全分析文档.
fit-check-task
查看任务的当前状态和进度.
fit-complete-task
标记任务完成并归档到 completed 目录.
fit-create-pr
创建 Pull Request.
research
Start or resume an academic research project — idea through literature, methodology, writing, feedback, and publishing.