elimination-research

elimination-research is a Structured reasoning & decision frameworks skill for AI agents, published by glebis in the claude-skills repository on GitHub. Skillspace rates elimination-research D (68/100) and it passed the safety scan; the rating is based on static analysis only.

This skill should be used for elimination-style research where the user wants to choose from a shortlist of products, tools, services, vendors, or other options using explicit criteria, numeric evidence, tournament-style comparison, source/domain classification, image-supported consumer reports, raw data tables, and ownership-cost estimates for replaceable parts. Use this skill whenever the user asks to compare options, buy something, shortlist candidates, rank alternatives, generate a "don't make me think" report, or produce a full audit report with raw numeric data.

Grade
D
Quality
68 / 100
Safety
Passed
GitHub stars
374

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
Not declared. Check the repository before reusing it.

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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