Verification

SkillMedia

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.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Verification skill

What this skill tells your AI

The instructions your AI receives, as published by dcc-mcp/dcc-mcp-core in python/dcc_mcp_core/skills/verification/SKILL.md and read by ahel’s review.

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, Sobel edge maps) live in dcc_mcp_core.verification as deterministic library functions, not skill tools, so callers gate on them directly.

Safety Contract

Every tool is read-only and side-effect free except make_comparison_sheet, which writes exactly one output image at the requested path. Tools never mutate the input captures and never launch a DCC. PPM/PGM inputs decode through the standard library; other formats (PNG/JPEG/EXR) decode through ffmpeg on PATH (or vx ffmpeg) and fail loudly when the decoder is unavailable.

Signals

GitHub stars
48
Forks
4
Last commit
Oct 2026
Advanced
Item type
skill
Key
verification-dcc-mcp
Source
github.com/dcc-mcp/dcc-mcp-core