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/behavioral-evals

@db14cdf
by google-geminigoogle-gemini/gemini-cli107k stars
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Guidance for creating, running, fixing, and promoting behavioral evaluations. Use when verifying agent decision logic, debugging failures, debugging prompt steering, or adding workspace regression tests.

Use this Skill: https://skilld.dev/gh/google-gemini/gemini-cli/behavioral-evals

This session only. Nothing lands on disk.

SKILL.md

≈55 tokens always: the name and description. ≈562 when used: this file. ≈3.5k more on demand in 4 files.

Behavioral Evals

Overview

Behavioral evaluations (evals) are tests that validate the agent's decision-making (e.g., tool choice) rather than pure functionality. They are critical for verifying prompt changes, debugging steerability, and preventing regressions.

[!NOTE] Single Source of Truth: For core concepts, policies, running tests, and general best practices, always refer to evals/README.md.


🔄 Workflow Decision Tree

  1. Does a prompt/tool change need validation?
    • No -> Normal integration tests.
    • Yes -> Continue below.
  2. Is it UI/Interaction heavy?
  3. Is it a new test?
    • Yes -> Set policy to USUALLY_PASSES.
    • No -> ALWAYS_PASSES (locks in regression).
  4. Are you fixing a failure or promoting a test?

📋 Quick Checklist

1. Setup Workspace

Seed the workspace with necessary files using the files object to simulate a realistic scenario (e.g., NodeJS project with package.json).

2. Write Assertions

Audit agent decisions using rig.setBreakpoint() (AppRig only) or index verification on rig.readToolLogs().

3. Verify

Run single tests locally with Vitest. Confirm stability locally before relying on CI workflows.


📦 Bundled Resources

Detailed procedural guides:

  • creating.md: Assertion strategies, Rig selection, Mock MCPs.
  • fixing.md: Step-by-step automated investigation, architecture diagnosis guidelines.
  • promoting.md: Candidate identification criteria and threshold guidelines.

Source: SKILL.md on GitHub

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    This skill provides a structured framework for behavioral evaluations, authored by a trusted vendor. It includes templates and procedural guides for testing agent decision logic. No security issues were detected.

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    Risk: LOW · No issues

Signed by skilld at db14cdf. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 6 months ago

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