agentleFS
Sign inStart free
rudrathegreatrudrathegreat/Astronomy-AI-Toolkit/skills/software_engineering/performance_optimizer/SKILL.md

performance-optimizer

Skill2 starsChanged 3 months agoNo licenceView on GitHub

Optimize scientific Python workloads with profiling, vectorization, compilation, and parallel execution.

17 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use observability-engineer, security-auditor and 5 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • xfstudioSkill

    observability-engineer

    Build production-ready monitoring, logging, and tracing systems.

    Also in 3 projects that use this

  • nahisahoSkill

    security-auditor

    security-auditor skill

    Also in 5 projects that use this

  • lodetomasiSkill

    database-optimizer

    Database performance optimization: N+1 detection, query analysis, indexing, and ORM tuning

    Also in 3 projects that use this

  • AutumnsGroveSkill

    api-designer

    Design and document RESTful and GraphQL APIs with OpenAPI/Swagger specifications, authentication patterns, versioning strategies, and best practices. Use for: (1) Creating API specifications, (2) Designing REST endpoints, (3) GraphQL schema design, (4) API authentication and authorization, (5) API versioning strategies, (6) Documentation generation

    Also in 3 projects that use this

  • GoogleSkill

    code-reviewer

    Also in 5 projects that use this

  • xenitV1Skill

    clean-code

    Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments

    Also in 3 projects that use this

The file

Create a free account to mount

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free