Home / dcc-mcp / dcc-mcp-core · python/dcc_mcp_core/skills/verification/SKILL.md · GitHub

verification skillA

verification is agent-read markdown (skill) from dcc-mcp/dcc-mcp-core: Cross-DCC verification toolset - deterministic capture review views, in-band image statistics, scene-vs-spec validation, and reference-vs-render comparison sheets. Pure Python, read-only, DCC-agnostic. Use to close the quality loop without shipping pixels to a model: flag white/near-black/gamma-broken frames from stats alone and catch missing-UV/missing-part exports before export. Not for scoring or aesthetic review - this toolset packages evidence and computes no scores..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Verification

A cross-DCC, read-only verification toolset (`affinity: any`) that closes the
capture-and-look quality loop with deterministic, machine-checkable signals.
Inspired by img2threejs's "deterministic-first, model-last" review design, it
computes evidence in-band — statistics, hashes, and verdicts — and never ships
pixels to a model unless a caller explicitly asks for `image`/`both` payloads.

The four tools map to the four legs of the deterministic capture contract:

- `capture_review_views` — the fixed front / side / top / three-quarter view
  plan, viewport-only, fails loudly on a missing, wrong-size, or blank frame.
- `image_stats` — mean luma, stddev, histogram, uniformity, and bad-frame flags
  (white playblast, near-black render, missing display transform).
- `validate_scene_vs_spec` — hierarchy names, material bindings, per-mesh UV
  coverage, part existence, non-manifold, and Euler checks, before export.
- `make_comparison_sheet` — reference + renders side-by-side into one image;
  packages evidence and computes no scores.

Pixel-level metrics (pHash / dHash / aHash, silhouette IoU, SSIM, CIEDE2000,
…

Read the whole file at its exact version.

How to install

Latest version
mdr add dcc-mcp/dcc-mcp-core/verification@git:20260918.50d62cb
Exact content
mdr add dcc-mcp/dcc-mcp-core/verification@sha256:69990dad0ed6bcff

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_kiretaiz4l4f4chd.svg)](https://markdownregistry.com/a/art_kiretaiz4l4f4chd)

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Versions

versioncommittedcommitsizeaudit
git:20260918.50d62cb latest2026-09-18 50d62cb 2,700 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (2700 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

dcc-mcp/dcc-mcp-core · 47 stars · license MIT · pushed 2026-09-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_kiretaiz4l4f4chd
GET https://markdownregistry.com/api/v1/resolve?ref=dcc-mcp/dcc-mcp-core/verification
GET https://markdownregistry.com/api/v1/blob/69990dad0ed6bcff6096794dac4b249abd8180b5de45dc9cd8ce941188f119ad

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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