research-reporting
research-reporting is a Model training & evaluation skill for AI agents, published by ProfSynapse in the Synaptic-Tuner repository on GitHub. Skillspace rates research-reporting C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Create structured research notes from experiment runs and analysis artifacts. Use when creating a note at run launch, updating it as training/evaluation/loss stages finish, summarizing a finished run, comparing experiment outcomes, extracting hypotheses from eval/loss artifacts, or proposing next-run actions grounded in `.tracking/experiments/<id>/analysis/` outputs. This skill is about turning repo-native experiment evidence into stable, machine-readable markdown.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 26
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.
Our review
- Architecture
- 96 / 100
- Maturity
- Structured: ships references or scripts
- 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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