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judgment

judgment

github.com/judgmentlabsTesting & quality048 installsUpdated 3d ago
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About judgment

Judgment is an agent-development skill for instrumenting applications, evaluating outputs, testing agent changes, and consulting current documentation. It emphasizes tracing real execution paths and choosing scorers suited to each evaluation.

Key features

  1. 01Application tracing guidance
  2. 02Evaluation setup and scorer selection
  3. 03OfflineTracer agent testing
  4. 04Python Code judge guidance
  5. 05Judgment documentation references

Use cases

  1. 01Adding tracing to an application
  2. 02Evaluating agent outputs with suitable scorers
  3. 03Testing model or prompt changes offline
  4. 04Creating deterministic Code judges

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/judgmentlabs/skills --skill judgment

After installing, type/judgmentin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
agent-testing.md
code-judges.md
docs.md
evaluations.md
tracing.md

Details

From the project README

Judgment

This skill helps you use Judgment effectively across common agent development workflows: instrumenting applications, evaluating outputs, creating Code judges, and looking up current Judgment docs.

Core Principles

Follow these principles for all Judgment work:

  1. Docs first: Fetch current Judgment docs and refer to reference files before implementing SDK patterns from memory.
  2. Instrument the real path: Add tracing to the functions, tools, and LLM calls the app actually executes.
  3. Tracing first for integrations: When the user asks to add Judgment to an app, start with references/tracing.md unless they explicitly ask for evaluations or Code judges.
  4. Stay on the tracer surface: In most cases, use Judgment's tracer, wrappers, and documented integrations directly. Do not reach into underlying provider objects or create additional wrapper layers unless the current docs require it or a real instrumentation gap remains after using the supported integration.
  5. Start small: For evaluations, begin with a focused example set and one scorer before expanding.
  6. Use the right scorer: Use Agent judges for rubric-based judgment and Python Code judges for deterministic logic, custom dependencies, or trace inspection.
  7. Keep credentials out of chat: Ask the user to set JUDGMENT_API_KEY and JUDGMENT_ORG_ID locally rather than pasting secrets.
  8. Use offline agent tests before production changes: For model, prompt, tool, or agent config changes, pull a stable dataset, collect fresh OfflineTracer traces for each input, then evaluate the generated offline examples in one batch. If the production agent is already traced with Judgment, leave that tracing intact and swap only the test harness initialization to client.offline_tracer(...).

Use Case References

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