theory-fidelity
theory-fidelity is a Structured reasoning & decision frameworks skill for AI agents, published by haabe in the mycelium repository on GitHub. Skillspace rates theory-fidelity D (65/100) and it passed the safety scan; the rating is based on static analysis only.
Audit whether the theories/methodologies a project claims to implement are faithfully operationalized — or name-dropped, partially built, distorted, or over-claimed. Source-grounds the load-bearing theories; tags the rest provisional. Run periodically alongside /framework-health.
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 39
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
- 94 / 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.