ai-agents-research-frontier
ai-agents-research-frontier is an Engineering planning & specs skill for AI agents, published by rjmurillo in the ai-agents repository on GitHub. Skillspace rates ai-agents-research-frontier B (85/100) and it passed the safety scan; the rating is based on static analysis only.
Three ranked open research programs for this repo, each with honest current-state evidence, first concrete steps, and a falsifiable milestone. Verified governance (ADR-069, proposed), cross-harness abstraction (ADR-072 and ADR-068, proposed), and the self-improving loop (issue #1345). Use when you say `research frontier`, `open problems`, `what should we research next`. Do NOT use for how to run an experiment here (use `ai-agents-research-methodology`).
- Grade
- B
- Quality
- 85 / 100
- Safety
- Passed
- GitHub stars
- 38
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
- 96 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- 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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