annotate
annotate is an LLM evaluation & observability skill for AI agents, published by glebis in the claude-skills repository on GitHub. Skillspace rates annotate D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Build and verify a PII gold set with HUMAN annotators (first-class). Launch the browser annotator, label spans per the codebook, export per-annotator label files, then compute inter-annotator agreement (Cohen's/Fleiss' kappa) and draft an adjudicated gold. Use when the user says "annotate PII", "label this transcript", "build a gold set", "inter-annotator agreement", "review annotations", "adjudicate labels", or wants to measure/defend a de-identification gold standard. Local-only: synthetic or consented data only; annotators' names and transcript text stay on the machine — only labels/stats are collected, nothing PII is re-shared.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 374
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
- No issues found
- License
- Not declared. Check the repository before reusing it.
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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