opd-tuning
opd-tuning is a Model training & evaluation skill for AI agents, published by redai-infra in the Relax repository on GitHub. Skillspace rates opd-tuning D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Tune Relax On-Policy Distillation (OPD/MOPD) runs — teacher SGLang engine knobs, logits-memory limits, student/teacher GPU split, and multimodal caches. Use when a user asks to speed up or debug an OPD run, mentions "OPD", "MOPD", "on-policy distillation", "蒸馏", a teacher engine OOM, teacher timeouts, idle student/teacher GPUs, or any `--teacher-sglang-*` / `--opd-*` flag. Produces a diagnosis report with cited flags, measured evidence, and concrete fixes; applies the edits only when asked.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 604
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
- 100 / 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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