agentic-eval SKILL.md skillA
agentic-eval from pr-e/openclaw-master-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add pr-e/openclaw-master-skills/agentic-eval@git:20260302.9834b38Pins git:20260302.9834b38 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- pr-e/openclaw-master-skills
- Path
skills/agentic-eval/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260302.9834b38, committed Mar 2, 2026
- Size
- 5,940 bytes
- Repository stars
- 3
- License
- MIT
Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Agentic Evaluation Patterns
Patterns for self-improvement through iterative evaluation and refinement.
## Overview
Evaluation patterns enable agents to assess and improve their own outputs, moving beyond single-shot generation to iterative refinement loops.
```
Generate → Evaluate → Critique → Refine → Output
↑ │
└──────────────────────────────┘
```
## When to Use
- **Quality-critical generation**: Code, reports, analysis requiring high accuracy
- **Tasks with clear evaluation criteria**: Defined success metrics exist
- **Content requiring specific standards**: Style guides, compliance, formatting
---
## Pattern 1: Basic Reflection
Agent evaluates and improves its own output through self-critique.
```python
def reflect_and_refine(task: str, criteria: list[str], max_iterations: int = 3) -> str:
"""Generate with reflection loop."""
output = llm(f"Complete this task:\n{task}")
for i in range(max_iterations):
# Self-critique
critique = llm(f"""
Evaluate this output against criteria: {criteria}
Output: {output}
Rate each: PASS/FAIL with feedback as JSON.
""")
…Read the whole file at its exact version.
How to install
mdr add pr-e/openclaw-master-skills/agentic-eval@sha256:fb198a5c9b12e746The line at the top of this page pins the label git:20260302.9834b38, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_dcgpz24mhvz6z4uk)
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Versions
The registry has recorded 1 version of this file, committed on Mar 2, 2026.
Audit of the latest version
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- pass: No instruction to send local credentials anywhere
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Source
pr-e/openclaw-master-skills · 3 stars · license MIT · pushed 2026-10-13 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_dcgpz24mhvz6z4uk GET https://markdownregistry.com/api/v1/resolve?ref=pr-e/openclaw-master-skills/agentic-eval GET https://markdownregistry.com/api/v1/blob/fb198a5c9b12e746d01a43c9ff3368598fdc1134bb458766f580186f31001573
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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