forgecad-reconstruct-from-images

forgecad-reconstruct-from-images is a skill for Codex from ForgeCAD/forgecad-public-kit. It costs 32 tokens per session (1,045 once invoked), scanned A, original, MIT.

A method for rebuilding a real, editable ForgeCAD object from reference images, where ForgeCAD is a tool for creating parametric 3D models with code.

In plain words
What is it for?
Use it to infer and build the complete object from front, back, side, top, bottom, cutaway, exploded, or transparent reference images.
Why use it?
It prevents a model from matching only one picture while being incomplete or inconsistent from other viewpoints.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to infer and build the complete object from front, back, side, top, bottom, cutaway, exploded, or transparent reference images.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images
Install

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.

Any agent
npx skills add ForgeCAD/forgecad-public-kit --skill forgecad-reconstruct-from-images
Clone the repo
git clone --depth 1 https://github.com/ForgeCAD/forgecad-public-kit

Made for: Codex.

Wrote 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.

agentmods badge for forgecad-reconstruct-from-images

README.md
[![agentmods](https://agentmods.dev/badge/skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images/github.svg)](https://agentmods.dev/skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images)
Your own site
<a href="https://agentmods.dev/skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images"><img src="https://agentmods.dev/badge/skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images/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.

agentmods 80×15 button for forgecad-reconstruct-from-images

Your own site · 80×15
<a href="https://agentmods.dev/skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images"><img src="https://agentmods.dev/badge/skills/forgecad/forgecad-public-kit/forgecad-reconstruct-from-images.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,045 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.01045
Opus 5 $0.00016 $0.00522
Sonnet 5 $0.00006 $0.00209
Haiku 4.5 $0.00003 $0.00104

Measured 11d ago against content hash 4106fd3ed7f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

forgecad-reconstruct-from-images 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/compare_images.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/forgecad-reconstruct-from-images/SKILL.md · 51 lines

How it starts

The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reconstruct From Images

The reference image is evidence, not the deliverable. The deliverable is a real parametric object that holds up from front, back, side, top, bottom, and reference camera views — a model that matches one image but falls apart from other angles has failed, even if the comparison board looks close. Cutaway, sectioned, exploded, or transparent references are evidence about the complete object: build the closed artifact and recreate explanatory views with viewer/inspection tools (the main forgecad skill's closed-artifact rule applies).

Companion Skills

  • forgecad — API docs, model authoring, renderer behavior.
  • forgecad-design-spec — when the images underdetermine artifact family, process posture, scale, operating story, or validation boundary.
  • forgecad-build-model — file placement, project structure, decomposition, definition of done.
  • forgecad-inspect-model — pre-delivery inspection for multi-part, internal, mechanical, thin-wall, or fit-sensitive objects.

Core Rule

Infer the real object before matching any camera — identity, manufacture, scale, what hidden sides must contain, what geometry must exist for physical coherence. Reference matching is a validation step after the object exists; never start by chasing pixels or the prettiest view.

Workflow

  1. Stage references in /tmp/<slug>-replicate/refs, keeping originals and adding view names where possible (front, side, rear-iso, top, detail).
  2. Read each image as evidence, recording: visible facts; scale cues; camera cues; unknowns (hidden/occluded geometry); conflicts across images or stylization.
  3. Write a Real Object Brief — a hard gate before modeling: (a) artifact identity + operating story; (b) assumed scale and units; (c) process posture + part/BOM boundary (real geometry vs purchased vs ghost vs omitted); (d) inferred hidden-side geometry + expected canonical front/back/left/right/top/bottom forms; (e) validation views and inspection evidence. Use forgecad-design-spec when these are underdetermined.
  4. Build a coarse 3D blockout — model the object, not the image: large volumes, axes, symmetry, side depth, rear form, underside, hidden continuations. Render canonical views before any reference-camera comparison. Follow forgecad-build-model for project structure.
  5. Calibrate one camera per usable reference, only after the blockout makes sense from canonical views. Use the object center as target; estimate azimuth/elevation/distance/FOV from visible faces and perspective cues; use orthographic when parallel edges stay parallel with no perspective convergence.
  6. Render comparison boards: render the model from each calibrated reference camera and place it next to the original. Never compare from memory.
  7. Iterate one class of change at a time, in order: object hypothesis → major proportions → canonical geometry → camera → details → presentation. If improving one reference view makes another view or a canonical render worse, the object hypothesis is wrong — fix the model, not the camera illusion.
  8. Use every image as a constraint. Never pick one target image and ignore the rest: assign each image a camera, evidence list, and confidence; optimize one shared geometry against the whole set; state how distorted or decorative images were weighted.
  9. Validate the final object: forgecad run, reference comparison boards, canonical renders, and targeted inspections via forgecad-inspect-model.

Read the full file on GitHub · 51 lines

Files

What ships with it

2 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.

Changes

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.

  1. 11d ago First seen · 51 lines · 32 tokens per session scan A 4106fd3ed7f8

Subscribe to this mod's changes

forgecad-reconstruct-from-images is a skill published in the GitHub repository ForgeCAD/forgecad-public-kit (931 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 1,045 once invoked, about $0.0002 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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