scanner-tuning
scanner-tuning is an Application security skill for AI agents, published by UnitOneAI in the SecuritySkills repository on GitHub. Skillspace rates scanner-tuning D (65/100) and it passed the safety scan; the rating is based on static analysis only.
Tunes vulnerability scanners to reduce false positives, optimize scan policies, and improve result accuracy. Covers false positive identification patterns, scan policy configuration, authenticated vs unauthenticated scanning tradeoffs, severity override criteria, plugin/check selection, scan scheduling, and result correlation across multiple scanners. Uses CVSS 4.0 for severity validation and CWE for vulnerability classification.
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 32
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
- 79 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 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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