forge-intake
Skill2 starsChanged 5 months agoNo licenceView on GitHub
Forge suite — physical-world and AI-world 3D intake. Converts real-world photo sequences into production-ready meshes or Gaussian splats (photogrammetry via COLMAP/Meshroom/ RealityScan), trains and exports Gaussian-splat / NeRF scenes (gsplat, Nerfstudio Splatfacto), and turns AI-generated raw geometry into clean, game-ready assets (Meshy/Tripo/TripoSR/Hunyuan3D → retopology + UV unwrap + texture rebake → GLB/FBX). Use whenever you need to: process a photo scan, run photogrammetry, reconstruct a 3D scene from images, train a Gaussian splat, convert a .ply splat file, generate 3D from a text prompt or reference image, clean up a raw AI-generated or scanned mesh, retopologise a dense scan, rebake textures off a raw scan, fix non-manifold geometry on raw capture, or make a raw scan/AI mesh game-ready. This is the INTAKE gate for raw scan/AI geometry only — for retopo/decimation/LOD of an EXISTING clean mesh use forge-topology; for PBR baking on a clean mesh use forge-texture. Produces validated GLB/FBX/PLY ready for downstream Forge skills. HEADLESS-FIRST: mesh tracks are driven from code and verified by reading a render PNG; splat tracks are verified by PSNR/SSIM (Open3D offscreen render needs a real GPU/OpenGL) and produce .ply/.sog; cloud AI tracks call vendor APIs over the network. Part of the Forge suite.
- Reads credentials
4 other projects use a version of this.
Adopted by
Most recently taken up by
- fabioalencar/forgedesigntheir own version, first seen Oct 20, 2026
- Dshamir/slm-forgetheir own version, first seen Oct 13, 2026
- ForgeyClap/claude-forgetheir own version, first seen Oct 11, 2026
- ForgeyClap/Forge-Coretheir own version, first seen Oct 11, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- ForgeyClap/claude-forge★ 2same name
- ForgeyClap/Forge-Core★ 2same name
- Dshamir/slm-forge★ 1same name
- fabioalencar/forgedesign★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository38 other files it gives its agents.
- atelier-componentsSkill
- atelier-copySkill
- atelier-dataSkill
- atelier-datavizSkill
- atelier-directionSkill
- atelier-foundationsSkill
- atelier-hardenSkill
- atelier-layoutSkill
- atelier-motionSkill
- atelier-perf-a11ySkill
- atelier-redesignSkill
- atelier-reviewSkill
- atelier-scrollSkill
- atelierSkill
- atelier-typographySkill
- atelier-uxSkill
- atelier-webglSkill
- codex-imagegenSkill
- codex-imagegen-tasteSkill
- forge-animateSkill
- forge-briefSkill
- forge-dataSkill
- forge-exportSkill
- forge-lightSkill
- forge-materialSkill
- forge-modelSkill
- forge-optimizeSkill
- forge-parametricSkill
- forge-proceduralSkill
- forge-renderSkill
- forge-rigSkill
- forge-simSkill
- forgeSkill
- forge-standardsSkill
- forge-textureSkill
- forge-topologySkill
- forge-uvSkill
- forge-validateSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
15 rules. 0 are common, 5 are distinctive, and 10 are very specific to this project.
0
Common
Most of the 4 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.