Layerlens Stratix Python Stratix Python

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:

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

Set your API key:

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.
2. Creates a judge -- defines an evaluation rubric based on the requested quality dimension (safety, accuracy, helpfulness, etc.).
3. Runs an evaluation -- scores the trace against the judge criteria.
4. 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:

# 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.

Source: LayerLens/stratix-python — distributed by TomeVault.