terminology-normalizer
terminology-normalizer is a Copy editing & proofreading skill for AI agents, published by WILLOSCAR in the research-units-pipeline-skills repository on GitHub. Skillspace rates terminology-normalizer D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Normalize terminology across a draft (canonical terms + synonym policy) without changing citations or meaning. **Trigger**: terminology, glossary, consistent terms, 术语统一, 统一叫法, 术语表. **Use when**: the draft has concept drift (same thing called 2–3 names) or global-review flags terminology inconsistency. **Skip if**: you are still changing the outline/taxonomy heavily (do that first). **Network**: none. **Guardrail**: do not add/remove citation keys; do not introduce new claims; avoid moving citations across subsections.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 487
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
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 1 collections
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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