Forgecad Inspect Model logo

Forgecad Inspect Model

Organization
ForgeCAD
forgecad-inspect-model

Select, run, and interpret ForgeCAD inspection evidence for collisions, sections, wall thickness, components, masks, depth, normals, surface continuity, and fit.

Overview

PublisherForgeCAD
Repositoryforgecad-public-kit
Skill nameforgecad-inspect-model
Stars
942
Forks
104
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ForgeCAD on GitHub. Read the source before you install it.

Installation

Install the Forgecad Inspect Model AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ForgeCAD/forgecad-public-kit/tree/mainline/skills/forgecad-inspect-model
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ForgeCAD/forgecad-public-kit.git /tmp/forgecad-public-kit
mkdir -p .claude/skills
cp -r /tmp/forgecad-public-kit/skills/forgecad-inspect-model .claude/skills/forgecad-inspect-model
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Forgecad Inspect Model in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Forgecad Inspect Model on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Forgecad Inspect Model is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Inspect Model

Use forgecad inspect ... when a shaded render is too ambiguous and you need structured evidence: a bundle directory with evidence PNGs plus a root manifest.json (or, for inspect section, a probe directory with result.json, section.svg, section.png). Inspection is not a substitute artifact: look inside with sections, masks, --focus/--hide, and transparency — never edit the model into a cutaway or exploded default to make inspecting easier. Output dirs: let inspect allocate its timestamped directory by default (repeated probes never collide); use /tmp/<model>-inspect for throwaway bundles, a project directory only for persistent artifacts.

Routing: authoring/API questions → forgecad skill; creating a new model → forgecad-build-model.

Workflow

  1. Identify the failure question. What would make the model wrong: overlap, thin walls, hidden cavity failure, disconnected or accidentally fused bodies, floating parts, orientation artifacts, identity confusion?

  2. Confirm the model executes. If in doubt, run forgecad run model.forge.js first; add --debug-imports for suspect imports.

  3. Pick ONE targeted evidence command from the table below. forgecad inspect evidence lists everything available.

  4. Summarize the manifest first, then use jq against manifest.json for targeted follow-up. The helper ships beside this SKILL.md — invoke it skill-dir-relative; it accepts the bundle directory or a manifest.json path:

    bash
    python <this-skill-dir>/summarize_manifest.py /tmp/model-inspect
  5. Inspect the PNGs, not only the JSON. View identity/context images first, then the risk evidence's view, then orthogonal cameras (front, right, top) when iso hides the issue, sections only when internals matter. In automation, resolve file paths through the manifest — custom cameras break canonical filenames.

  6. Isolate intentional overlaps with --focus "A,B" or --hide "C" so the remaining report stays meaningful.

  7. Treat findings as model bugs: unexpected collisions, critical thin regions, high unresolved thickness area, wrong component counts, floating bodies, or surprising gaps mean fix the model and reinspect.

  8. Report honestly. Include the exact command, bundle path, manifest highlights, and the PNG views actually inspected. Never claim geometry is verified if you only ran forgecad run.

Evidence Selection

QuestionEvidence command
Quick visual sanityinspect visual image
Kinematic rig, joints, axes, and linksinspect visual rig
Object naming and identityinspect visual objects
Exact local section measurement, bore widths, rib thickness through a chosen lineinspect section --ray ...
Hidden internals, cavities, pockets, screw paths, captured componentsinspect sections at|stack|sample
Multi-part interference, fit checks, ghost parts, moving clearancesinspect fit interference
Printability, shell walls, ribs, bosses, snaps, slotsinspect manufacture thickness plus inspect sections at|stack|sample when internals matter
Parts without a mesh-contact path to the groundinspect physical floating
Accidental fusion, connected solidsinspect physical components
Air gaps between physical componentsinspect physical gaps
Surface orientation, occlusion, faceting, strange protrusionsinspect visual depth or inspect visual normals
Loft, fillet, skin, and sweep surface continuityinspect surface zebra or inspect visual normals
Reference-vs-candidate reconstruction comparisoninspect compare overlay --with reference.3mf

Section Probe + Replay

The agent-native measure-then-recheck loop:

bash
forgecad inspect section model.forge.js --plane yz --ray bore:-20,0:20,0
forgecad inspect replay outputs/inspect/<probe>/result.json --source candidate.forge.js

The probe's result.json field contract (frames, rulers, gaps, replaySpec) is documented in the forgecad skill's docs/guides/inspection-bundles.md.

Misread Traps

  • Face-touching is not a collision; collision findings are positive-volume overlaps.
  • Gray/unresolved thickness area means the evidence is incomplete, not that the model is safe.
  • Distance/gap figures are bbox-gap metrics between components, not closest-surface distances.
  • Depth, normals, and zebra are visual aids (heatmap, camera-view normals, stripe shader), not exact measurements or curvature proofs.
  • Resolve mask colors through the manifest's object list, never by object order.

Reference

Bundle/manifest contract, evidence semantics, and current limits: the forgecad skill's docs/guides/inspection-bundles.md. CLI flags and command tree: its docs/CLI.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Forgecad Inspect Model AI skill do?

Select, run, and interpret ForgeCAD inspection evidence for collisions, sections, wall thickness, components, masks, depth, normals, surface continuity, and fit.

Why use Forgecad Inspect Model on TypingMind?

Because you install it once and use it with any model. Forgecad Inspect Model is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Forgecad Inspect Model in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ForgeCAD/forgecad-public-kit/tree/mainline/skills/forgecad-inspect-model. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Forgecad Inspect Model?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Forgecad Inspect Model?

As many as you like. As long as a model supports skills, you can use Forgecad Inspect Model with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Forgecad Inspect Model AI skill free?

Yes. It is published on GitHub by ForgeCAD under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇