AI Tools Catalog
HOW WE EVALUATE

Registry methodology

A transparent framework for compatibility, verification, quality signals and Skill Score.

Evidence first

We show what can be supported by source metadata, validation results and measured catalog activity. Missing evidence is not invented.

Compatibility labels

Native

Published in the original format used by a supported agent.

Converted

Generated from a normalized skill using a target-specific adapter.

Tested

Passed the current structural and behavioral checks for the target format.

Skill Score

New listings receive a bounded baseline score. The score can then change using measured activity such as views, installations and user ratings. Popularity is capped so it cannot fully replace quality evidence.

Security and permissions

Risk labels summarize declared permissions and available source signals. They are not a substitute for a security audit. Users should inspect scripts, network access, filesystem operations and required secrets before installation.

Corrections and updates

Authors and users can report inaccurate attribution, compatibility or licensing information through the contact page. Material corrections update the listing and its evidence.

Find once. Use with any agent.

Explore portable AI skills or publish your own skill in the universal registry.

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