layerlens/stratix-python/layerlens-skill

Claude Code and agent skill by layerlens/stratix-python

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Evaluate AI outputs with LayerLens. Upload traces, create judges, run evaluations, and retrieve quality scores -- all from within OpenClaw.

Install

npx vskill@latest install layerlens/stratix-python/layerlens-skill

SKILL.md

LayerLens Skill for OpenClaw

This skill lets OpenClaw interact with the LayerLens AI evaluation platform. Use it to upload traces of agent executions, create quality judges, run evaluations, and retrieve scored results.

Prerequisites

Install the LayerLens Python SDK:

bash
pip install layerlens --index-url https://sdk.layerlens.ai/package

Set your API key:

bash
export LAYERLENS_STRATIX_API_KEY=your-api-key

What This Skill Does

When triggered, this skill:

  1. Uploads a trace -- captures the input (task) and output (agent response)

as a LayerLens trace with metadata about the execution context.

  1. Creates a judge -- defines an evaluation rubric based on the requested

quality dimension (safety, accuracy, helpfulness, etc.).

  1. Runs an evaluation -- scores the trace against the judge criteria.
  2. Returns results -- provides a pass/fail verdict, numeric score, and

reasoning explanation.

Usage

Ask OpenClaw to evaluate an output:

Evaluate the last response for safety using LayerLens.
Run a quality check on this output: "The capital of France is Berlin."
Upload a trace of our conversation and score it for helpfulness.

Evaluation Script

The skill delegates to scripts/evaluate.py, which accepts input via stdin or command-line arguments:

bash
# Via arguments
python scripts/evaluate.py --input "What is 2+2?" --output "2+2 is 4." --goal "factual accuracy"
# Via stdin (JSON)
echo '{"input": "What is 2+2?", "output": "2+2 is 4.", "goal": "factual accuracy"}' | python scripts/evaluate.py

SDK Reference

The skill uses these LayerLens SDK methods:

  • client.traces.upload(path) -- upload a JSONL trace file
  • client.judges.create(name=, evaluation_goal=) -- create an evaluation judge
  • client.trace_evaluations.create(trace_id=, judge_id=) -- run an evaluation
  • client.trace_evaluations.get_results(evaluation_id) -- retrieve results

See the LayerLens Python SDK documentation for full API details.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
276
Repository forks
235
7-day trend score
28

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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