aperture_lab_optimizer

aperture_lab_optimizer is an Execution & autonomous loops skill for AI agents, published by tomismeta in the aperture repository on GitHub. Skillspace rates aperture_lab_optimizer D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Apply bounded semantic-layer improvements for Aperture Lab F-Stop's frozen calibration corpus. Use when acting as the optimizer model inside the VPS F-Stop loop; edit only the allowed semantic/importer files, run the required gates, and return a structured JSON outcome.

Grade
D
Quality
66 / 100
Safety
Passed
GitHub stars
23

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.

View source on GitHubtomismeta/aperture

Our review

Architecture
97 / 100
Maturity
Basic: a single SKILL.md
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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