ai-research
ai-research is a Web research & fact-checking skill for AI agents, published by arcasilesgroup in the ai-engineering repository on GitHub. Skillspace rates ai-research D (64/100) and it passed the safety scan; the rating is based on static analysis only.
External evidence with citations via a 4-tier escalation (local → free MCPs → web/Exa → NotebookLM autonomous deep research, launched first / harvested last). Every claim sourced [N] or marked [unsourced]; output ends with 3 cited recommended directions. Trigger for 'what does the state of the art say about', 'compare options for', 'find sources on', 'investigate this question', 'research this'. Use for questions whose answer lives OUTSIDE the codebase. Not for codebase exploration; use /ai-explore instead. Not for refactors; use /ai-simplify instead. Not for business-logic debugging; use /ai-debug instead.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 53
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
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 1 other repositories, in 1 collections
What the scanner flagged
- mentions secrets in text
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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