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-data-analysisgit 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-data-analysis)<a href="https://agentmods.dev/commands/hanhuark/mechanical-engineering-research-skill/me-data-analysis"><img src="https://agentmods.dev/badge/commands/hanhuark/mechanical-engineering-research-skill/me-data-analysis.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 | $0.00029 | $0.00184 |
| Opus 5 | $0.00015 | $0.00092 |
| Sonnet 5 | $0.00006 | $0.00037 |
| Haiku 4.5 | $0.00003 | $0.00018 |
Grade A, and why
me-data-analysis 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 Data Analysis
Use mechanical-engineering-research to plan or implement experimental, simulation, CFD, or AI-assisted data analysis.
Workflow:
- Start with a representative baseline case.
- Show the full raw-data to metric or figure pipeline on the baseline case.
- Define metrics, units, thresholds, filters, fitting windows, uncertainty, and sanity checks.
- Design hypothesis-driven DOE for experiments or simulations.
- Avoid broad parameter sweeps until the dominant mechanisms and useful ranges are known.
- Use plots to reveal mechanisms, not merely display data.
Expected output:
- baseline analysis plan
- DOE table or staged case matrix
- processing pipeline
- plotting plan
- validation and sanity checks
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 · 29 tokens per session scan A ecd2429fcad0
me-data-analysis is a command published in the GitHub repository hanhuark/mechanical-engineering-research-skill (16 stars, last pushed 8d ago), licensed MIT. It adds 29 tokens to every session and 184 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
research
Start or resume an academic research project — idea through literature, methodology, writing, feedback, and publishing.
openehr-explain
One-stop router that explains or looks up any openEHR thing — auto-detects an archetype, a template, an RM/AM/BASE type, an RM structural concept, an ADL idiom, an AQL query or keyword, or a terminology code (replaces /archetype-explain, /template-explain, /type-spec, /rm-structure, /adl-idiom, /terminology).
gpd:write-paper
Structure and write a physics paper from project research results or a bounded external-authoring intake.
gpd:derive-equation
Perform a rigorous physics derivation with systematic verification at each step.
gpd:limiting-cases
Systematically identify and verify all relevant limiting cases for a result or phase.
external-review
Run a single external code review via an external LLM API on the full branch diff vs main. Standalone usage — no aggregation with internal review.