sf-research-methodology

sf-research-methodology is a Structured reasoning & decision frameworks skill for AI agents, published by 91zgaoge in the StoryMoss repository on GitHub. Skillspace rates sf-research-methodology D (65/100) and it passed the safety scan; the rating is based on static analysis only.

把直觉变成被接受结果的纪律（证据门槛、假设须先报数字、idea 生命周期、好想法来源）。何时加载：要做研究/实验、要提一个新机制/新阈值、要把实验 flag 转为默认或退役、或被问“怎么验证/怎么让这个想法被接受”时。

Grade
D
Quality
65 / 100
Safety
Passed
GitHub stars
55

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHub91zgaoge/StoryMoss

Our review

Architecture
94 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
Not declared. Check the repository before reusing it.
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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