falsification-first-stress-test
falsification-first-stress-test is a Structured reasoning & decision frameworks skill for AI agents, published by yogsoth-ai in the de-anthropocentric-research-engine repository on GitHub. Skillspace rates falsification-first-stress-test D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Campaign: Truth-seeking adversarial validation for scientific research artifacts (NOT publication defense). Core question: Where have we fooled ourselves, and is each load-bearing claim even falsifiable? Win-condition is INVERTED from survival/resilience to active refutation. Methods: Popper falsificationism, Lakatos Proofs and Refutations, Mayo severe testing, Platt strong inference.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 386
Unproven: rated by static analysis only, not yet compared head-to-head.
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Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 1 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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