pydantic-evals SKILL.md skillA
pydantic-evals from fuenfgeld/pydantic-ai-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add fuenfgeld/pydantic-ai-skills/pydantic-evals@git:20260707.0a11b6bPins git:20260707.0a11b6b in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- fuenfgeld/pydantic-ai-skills
- Path
skills/pydantic-evals/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260707.0a11b6b, committed Jul 7, 2026
- First version recorded
- Jan 20, 2026
- Size
- 11,861 bytes
- Repository stars
- 10
- License
- MIT
Test and evaluate AI agents and LLM outputs using code-first evaluation framework with strong typing. Use when the user wants to: (1) Create evaluation datasets with test cases for AI agents, (2) Define evaluators (deterministic, LLM-as-Judge, custom, or span-based), (3) Run evaluations and generate reports, (4) Compare model performance across experiments, (5) Integrate evaluations with Pydantic AI agents, (6) Set up observability with Logfire, (7) Generate test datasets using LLMs, (8)…
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
# Pydantic Evals
## Overview
Pydantic Evals provides rigorous testing and evaluation for AI agents and LLM outputs using a code-first approach with Pydantic models. It enables "Evaluation-Driven Development" (EDD) where evaluation suites live alongside application code, subject to version control and CI/CD.
## Core Concepts
Understand these key primitives:
### Case
A single test scenario with inputs, optional expected output, and metadata.
```python
from pydantic_evals import Case
case = Case(
name="refund_request",
inputs="What is your refund policy?",
expected_output="30 days full refund",
metadata={"category": "policy"}
)
```
### Dataset
Collection of Cases with default evaluators. Generic over input/output types.
```python
from pydantic_evals import Dataset
dataset = Dataset(
name="my_eval_suite", # v2: name is REQUIRED (keyword-only)
cases=[case1, case2, case3],
evaluators=[evaluator1, evaluator2]
)
```
### Evaluator
Logic engine that assesses outputs. Returns bool (Pass/Fail), float/int (score), or str (label).
### Experiment
Point-in-time performance capture when Dataset runs against a Task.
…Read the whole file at its exact version.
How to install
mdr add fuenfgeld/pydantic-ai-skills/pydantic-evals@sha256:b72764f7fbf74c4fThe line at the top of this page pins the label git:20260707.0a11b6b, 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_4yuiluewhfpgukef)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Jan 20, 2026 and Jul 7, 2026, about one every 168 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260707.0a11b6b latest | 2026-07-07 | 0a11b6b | 11,861 B | A | view · diff |
| git:20260120.9fcbca9 | 2026-01-20 | 9fcbca9 | 10,614 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (11861 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
fuenfgeld/pydantic-ai-skills · 10 stars · license MIT · pushed 2026-10-17 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_4yuiluewhfpgukef GET https://markdownregistry.com/api/v1/resolve?ref=fuenfgeld/pydantic-ai-skills/pydantic-evals GET https://markdownregistry.com/api/v1/blob/b72764f7fbf74c4f5bbb243862602f4d31e77c8482dabae66a80d2febc02a971
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.