s4h-information-entropy
s4h-information-entropy is a Structured reasoning & decision frameworks skill for AI agents, published by human-avatar in the skills-for-humanity repository on GitHub. Skillspace rates s4h-information-entropy D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Measures uncertainty, surprise, and information content using Shannon entropy. Use when asked 'how much information does this actually contain', 'how uncertain is this source', 'is this result surprising', 'what should I update on', 'where is the real information in this dataset', or when you need to distinguish high-information from low-information inputs.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 201
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
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked 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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