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Agent tooling

muse-jev-playbook

Jev decision layer for Muse: a fast, cheap TypeSafe AI gate before expensive agent work — confidence policy, recipes, reference router, honest measurement.

How it uses Jev

Use TypeSafe AI's Jev as a cheap, fast decision layer inside an AI agent workflow — triage, classify, score, and gate work before expensive steps (browser, deep research, retries, subagents).

Use cases

  • choice "What kind of work does this need?" → research (confidence 0.93)
  • noul "Should we cap this research at 5 sources instead of going deep?" → yes (0.88)
  • score "How much effort is justified?" → Heavy (0.71)
Language
Python 100%
License
MIT
Last activity
Sep 2026
Added
2026-09-23
Stars at snapshot
16
Status
Community listing

Source: community catalog. Details and metrics reflect the published community snapshot and are not a performance endorsement. Documentation details extracted from GitHub · the README.

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