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 armpro24-blip/cad-cae-copilot --skill aieng-cad-cae-copilotgit clone --depth 1 https://github.com/armpro24-blip/cad-cae-copilotWrote 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/armpro24-blip/cad-cae-copilot/aieng-cad-cae-copilot)<a href="https://agentmods.dev/skills/armpro24-blip/cad-cae-copilot/aieng-cad-cae-copilot"><img src="https://agentmods.dev/badge/skills/armpro24-blip/cad-cae-copilot/aieng-cad-cae-copilot/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/armpro24-blip/cad-cae-copilot/aieng-cad-cae-copilot"><img src="https://agentmods.dev/badge/skills/armpro24-blip/cad-cae-copilot/aieng-cad-cae-copilot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00065 | $0.00798 |
| Opus 5 | $0.00032 | $0.00399 |
| Sonnet 5 | $0.00013 | $0.00160 |
| Haiku 4.5 | $0.00006 | $0.00080 |
Grade A, and why
aieng-cad-cae-copilot 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aieng-cad-cae-copilot
MCP-first CAE workflow discipline for agents operating the active AIENG Workbench. This skill teaches order of operations and claim discipline; it does not add solver capability.
Purpose
- Use package evidence and MCP tool returns as the source of truth.
- Prepare solver runs without inventing missing material, loads, or constraints.
- Keep
cae.run_solverbehind the approval boundary. - Report only evidence-backed results and explicit limitations.
- For repeatable loops, follow the relevant entry in
../engineering_skill_contracts.json:cae-preflight,solver-run-orchestrate,design-target-review, orevidence-report-synthesize.
When to use
Use for CAE readiness inspection, setup patching, solver preflight/deck generation, solver execution, FRD metric extraction, field-region extraction, and refreshed result summaries. Do not use for new CAD authoring or schema/tool implementation.
Required workflow
- Inspect state with
aieng.agent_context { project_id }and, when needed,aieng.inspect_packageoraieng.write_completeness_report. - If material, loads, or constraints are missing, ask the user or apply explicit setup with
cae.apply_setup_patch. - Run
cae.prepare_solver_run { project_id }before any solver execution. Use therecommended_next_callslist in the response to decide the nextcae.*call. - If the input deck is missing but setup is sufficient, call
cae.generate_solver_input { project_id }. - Call
cae.run_solver { project_id }only after successful preflight and only through approval. IfAIENG_MCP_BLOCK_APPROVAL_TOOLS=1is active, report the server refusal and stop. - After a successful solver run, call
cae.extract_solver_results, optionallycae.extract_field_regions, thenpostprocess.refresh_cae_summary. - Re-read context/results before reporting final numbers.
Credibility tiering
Every result-bearing output carries a single credibility stamp (the shared
V&V-40 tier). Ordered low → high: critique_finding < surrogate_prediction <
proxy_assembly_result < executed_solver_result. Read credibility.tier and
report it with the numbers; never present a lower tier as if it were an
executed-solver result. An output that claims a solver result without
solver_executed: true is downgraded to unverified (rank 0) with a
downgrade_reason — treat it as not solver-backed. production_ready is false
unless explicitly certified.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 61 lines · 65 tokens per session scan A 1d875e09d107
aieng-cad-cae-copilot is a skill published in the GitHub repository armpro24-blip/cad-cae-copilot (59 stars, last pushed 4d ago), licensed MIT. It adds 65 tokens to every session and 798 once invoked, about $0.0003 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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