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-authoringgit 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-authoring)<a href="https://agentmods.dev/skills/armpro24-blip/cad-cae-copilot/aieng-cad-authoring"><img src="https://agentmods.dev/badge/skills/armpro24-blip/cad-cae-copilot/aieng-cad-authoring/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-authoring"><img src="https://agentmods.dev/badge/skills/armpro24-blip/cad-cae-copilot/aieng-cad-authoring.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 | $0.00067 | $0.03660 |
| Opus 5 | $0.00034 | $0.01830 |
| Sonnet 5 | $0.00013 | $0.00732 |
| Haiku 4.5 | $0.00007 | $0.00366 |
Grade A, and why
aieng-cad-authoring 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 12d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aieng-cad-authoring
MCP-first CAD authoring discipline for agents driving the active AIENG Workbench. The recommended path is the live MCP toolchain and build123d runtime, not the older schema-plan CLI flow.
Purpose
- Create or extend real CAD geometry through
cad.execute_build123d. - Keep generated geometry inspectable with named parts, colors, and editable constants.
- Use the UI as the live 3D viewer and spatial pointer surface.
- Preserve evidence honesty: CAD output is geometry evidence, not engineering validation.
When to use
Use when the user asks to create, build, design, model, add, or substantially modify CAD geometry.
For pure dimensional tweaks on an existing editable model, prefer cad.edit_parameter.
For engineering audit only, use cad.critique without mutating geometry.
For solver workflows, use aieng-cad-cae-copilot.
Required workflow
- Call
aieng.agent_readme,aieng.list_projects, andaieng.agent_context { project_id }when project state is not already known. - Call
cad.get_source { project_id }before incremental edits; usemode="append"only whenhas_base=true. - For new/additive geometry, call
cad.execute_build123dwith build123d Python that:- binds the final model to
result, - omits export calls,
- sets
.labelon every meaningful part, - sets
.color = Color(r,g,b)for readability, - declares editable dimensions as
UPPER_SNAKE_CASEconstants, - asserts design intent with
require(condition, "message")— e.g.require(WALL_THICKNESS >= 3, "wall below 3mm CNC minimum"). A failedrequire()(or a bareassert) fails the build deterministically and is returned as a structuredcode: design_rule_violation, so constraints are verified by construction instead of hoped for; a passing one is a no-op.
- binds the final model to
- Inspect the returned thumbnail,
named_parts,parts_added,geometry_report_summary, symmetry, and gaps before continuing. - For pure dimensional changes, use
cad.edit_parameterand read bothregression_diff(topology drift) andcritique_diff(manufacturability) before trusting the result. - For mechanical parts, call
cad.critiqueafter creation and fix blocking manufacturability findings.
What ships with it
9 files 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.
- agents/openai.yaml 176 B
- references/backend-policy.md 2.1 KB
- references/clarification-policy.md 2.0 KB
- references/decision-policy.md 1.5 KB
- references/evidence-claim-policy.md 1.3 KB
- references/failure-recovery.md 1.5 KB
- references/modeling-plan-rules.md 2.1 KB
- references/output-format.md 2.0 KB
- references/workflow.md 3.4 KB
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.
- 12d ago First seen · 228 lines · 67 tokens per session scan A 037eb3f8ed58
aieng-cad-authoring is a skill published in the GitHub repository armpro24-blip/cad-cae-copilot (59 stars, last pushed 4d ago), licensed MIT. It adds 67 tokens to every session and 3,660 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.
Other skills, from other repositories
simplecadapi
Build, assemble, inspect, reconstruct, and export parametric CAD models with the SimpleCADAPI Python SDK. Use for SimpleCAD geometry modeling, constrained sketches, parts and assemblies, standard gears and bearings, STEP/BREP inspection and reconstruction, durable product packages, model JSON replay, and CAD backend…
b123d-modeling
Use this skill when asked to model, build, or modify a 3D part or assembly with build123d — from a text description, a technical drawing (image or PDF), dimensions in a spec, or an existing STEP/STL file.
kernelcad-authoring
Author or modify kernelCAD models in TypeScript. Scripts live in .kcad.ts files; the kernelCAD CLI (kernelcad evaluate and kernelcad export stl|step|dxf|3mf|glb -o ) executes them via an OpenCASCADE WASM kernel.
kernelcad-mcp
Load when kernelcad mcp is available and you need to inspect or edit a live model without re-running the full CLI on every change. The MCP server exposes dynamic introspection tools that operate on evaluated in-memory state.
kernelcad-features
Edge and face features — fillet, chamfer, shell, face refs through operations, holes, cutouts. Use when adding rounded edges, recesses, bolt patterns, or carved profiles to a kernelCAD model.
kernelcad-kinematic
Use when verifying whether a moving assembly is buildable — sampled-pose collision sweeps across joint ranges, IK reachability for end-effector targets, mounting-hole fastener consistency, and static-load capacity on cantilever-shaped parts. Loads alongside kernelcad-authoring to gate design-time mechanism feasibility.