lightx2v-native-model-porting
lightx2v-native-model-porting is a Model training & evaluation skill for AI agents, published by ModelTC in the LightX2V repository on GitHub. Skillspace rates lightx2v-native-model-porting F (51/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill when adding native LightX2V support for a new model or task: understand an upstream inference repo, map it onto LightX2V runner/model/weight/infer/scheduler/input-encoder/VAE conventions, convert or load weights, add configs and Wan-style scripts without hard-coded paths, implement CFG/KV cache/block-model offload/SP/CFG-parallel without batch dimensions, and verify output parity with the upstream pipeline.
- Grade
- F
- Quality
- 51 / 100
- Safety
- Passed
- GitHub stars
- 2,806
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 76 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
What the scanner flagged
- mentions secrets in text
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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