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 skills add Cai-aa/CAE-Agent-Hub --skill calculix-femgit clone --depth 1 https://github.com/Cai-aa/CAE-Agent-HubWrote 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/skills/cai-aa/cae-agent-hub/calculix-fem)<a href="https://agentmods.dev/skills/cai-aa/cae-agent-hub/calculix-fem"><img src="https://agentmods.dev/badge/skills/cai-aa/cae-agent-hub/calculix-fem/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cai-aa/cae-agent-hub/calculix-fem"><img src="https://agentmods.dev/badge/skills/cai-aa/cae-agent-hub/calculix-fem.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 10 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00079 | $0.00622 |
| Opus 5 | $0.00039 | $0.00311 |
| Sonnet 5 | $0.00016 | $0.00124 |
| Haiku 4.5 | $0.00008 | $0.00062 |
Grade A, and why
calculix-fem 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 13d 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
CalculiX FEM
CalculiX (ccx) is an open-source FEM solver (GPLv2, no license). It reads
Abaqus-style .inp decks and writes text .dat results plus .frd field output.
ccx returns exit code 0 even on *ERROR, so never judge success by the exit
code — the solver layer checks stdout for *ERROR and requires a data row in the
.sta.
When to Use
Use this skill when an agent must run an open-source linear-static FEA analysis on
CalculiX: parse/inspect a .inp deck, tune section/material/load parameters, solve
with ccx, read .dat results, or export a viewer-renderable result. For commercial
solvers (Abaqus/Ansys), use those solvers' own skills instead.
Workflow
fea_health— confirm meshio is available andccxis detected.parse_inp— inspect the.inp(nodes, elements, sections, materials, loads).list_design_vars_tool— list tunable variables; each carries avar_id.modify_card_tool— change a variable byvar_id(pure-text, in place).run_solver_tool— submit the deck toccx.read_results_tool— read max von Mises (self-computed), max |U|, volume, mass.export_results_tool— writeresult_mesh.jsonfor the viewer.
Rules
- Units follow the
.inpworking system (commonly mm-t-s-MPa). Report them. .dathas no von Mises column and no total volume/mass — these are derived.- Never rewrite a deck with
meshio.write(it drops cards and corrupts element types). Usemodify_card_tool. - For the deck to produce both text results and the field output the viewer needs,
include
*NODE PRINT/*EL PRINT(for.dat) and*NODE FILE/*EL FILE(for.frd).
Example
MCP/CalculiX/examples/cantilever.inp is a public cantilever benchmark (steel
C3D8 solid bar, clamped end, transverse tip load). Hand-calc targets at P = 100 N:
tip deflection ≈ 0.8 mm, root stress ≈ 140 MPa.
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.
- 13d ago First seen · 46 lines · 79 tokens per session scan A 12a71c930404
calculix-fem is a skill published in the GitHub repository Cai-aa/CAE-Agent-Hub (881 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 622 once invoked, about $0.0004 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.
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