nvidia-omniverse/usd-content-agents/content-texture-quality
Claude Code and agent skill by nvidia-omniverse/usd-content-agents
- community
Checking that the SKILL.md file is still in the repository.
Collect matched Texture evidence, optionally request advisory critique, and record the outer multimodal review. Use after explicit candidate generation.
Install
npx vskill@latest install nvidia-omniverse/usd-content-agents/content-texture-qualitySKILL.md
Texture Quality Review
Collect fresh paired source/candidate evidence for the exact target set, then let the outer multimodal reasoner decide accept, reject, or revise. Domain VLM critique is an independently selected advisory leaf.
When to Use
Use after every initial or refined candidate application.
Limitations
- Semantic claims require actual rendered evidence.
- Validation cannot alter the output asset.
- Validator/VQA findings cannot directly partition canonical accepted and
remaining IDs.
- Every disposition must be authored in an outer review artifact bound to the
exact candidate result and fresh evidence.
Prerequisites
The frozen operation selection must request evidence and review, and the generation packet must bind the output asset. critique may be requested or explicitly not_requested.
Instructions
- Render every matching selected and canonical view through the shared OVRTX
USD path, preserving the exact source USD digest and OVRTX render metadata with each evidence record.
- Verify unchanged geometry, bindings outside scope, source dependency
identity, candidate closure, target UV/material state, and reference bytes.
- Stop after
texture evidence. It must report semantic assessment as
not_evaluated, not pass.
- Only when selected, run
texture critiquewith explicit VLM backend and
model. Treat findings as advisory evidence, never the semantic decision.
- Have the outer model directly inspect every exact reference, then every
outer-provided image, then every matched source/candidate image, in that exact order. Author one accept, reject, or revise for every exact unit, binding the candidate result/output digest and evidence digest.
- Record that decision with
texture review. Fail closed on visual rejection,
stale evidence, missing units, or candidate substitution. Only explicit outer revise units may be regenerated.
- Stop when all units have outer acceptance or the bounded budget is exhausted.
Command Reference
Run content-workflow-cli texture evidence first. If selected, run content-workflow-cli texture critique with explicit provider configuration. Finally author texture-outer-review-input.v1 and run content-workflow-cli texture review.
Common Workflows
If one unit fails, load content-texture-scope and content-texture-candidate for only that unit; do not replay successful work.
Output Format
Retain texture_candidate_evidence.json, optional texture_critique.json, and texture_outer_review.json with paired renders, references, renderer metadata, static findings, provider provenance, candidate identity, and outer dispositions.
Troubleshooting
Reject validation output that omits requested IDs, adds IDs, changes order, references a different asset, or reports a stale iteration.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingagentic/.agents/skills/content-texture-quality/SKILL.md
Popularity
- Repository stars
- 205
- Repository forks
- 25
- 7-day trend score
- 27
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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