autodecision
autodecision is a Multi-agent review & consensus skill for AI agents, published by harshilmathur in the autodecision repository on GitHub. Skillspace rates autodecision C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Auto-Decision Engine: iterative decision simulation using autoresearch principles and a persona council. Decomposes decisions, generates competing hypotheses, simulates first/second-order effects with probabilities, critiques via anonymized peer review, and iterates until insights stabilize mechanically. The output is a possibility map — hypotheses, effects, council disagreements, adversarial scenarios, assumptions — with a recommendation synthesized at the end, not as the product.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 93
Unproven: rated by static analysis only, not yet compared head-to-head.
Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it looks written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
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
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 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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