fuzzing
fuzzing is an Integration & environment testing skill for AI agents, published by Vyntra-Research in the Proteus repository on GitHub. Skillspace rates fuzzing D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Design calibrated fuzzing, differential probes, harnesses, and oracles for narrow Proteus surfaces. Use when the goal is to learn how inputs affect parsers, state machines, adapters, runtimes, or side effects, not to spray generic payloads.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 27
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
- GPL-3.0
- 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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