evaluation-methodology SKILL.md skillA
evaluation-methodology from wshobson/agents is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add wshobson/agents/evaluation-methodology@git:20260926.11f75d8Pins git:20260926.11f75d8 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- wshobson/agents
- Path
plugins/plugin-eval/skills/evaluation-methodology/SKILL.md- Versions recorded
- 4
- Latest version
- git:20260926.11f75d8, committed Sep 26, 2026
- First version recorded
- Mar 25, 2026
- Size
- 7,908 bytes
- Repository stars
- 42,320
- License
- MIT
PluginEval quality methodology, covering dimensions, rubrics, and scoring formulas. Use this skill when understanding how plugin quality is measured, when interpreting a low score on a specific dimension, when deciding how to improve a skill's triggering accuracy or orchestration fitness, when setting score thresholds for your marketplace, or when explaining quality badges to external partners like Neon.
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
# Evaluation methodology PluginEval scores a skill or a plugin from 0 to 100 by combining up to three layers. The static layer is a lint. It's fast and deterministic, and it's useful for checking structure. The LLM judge and Monte Carlo layers are experimental, not validated against human labels, so treat their numbers as rough signals. For the trace-based eval program, see `evals/README.md` at the repository root. The judge rubric anchors are in [references/rubrics.md](references/rubrics.md). Fixes for each anti-pattern and tips for each dimension are in [references/improving-scores.md](references/improving-scores.md). ## Evaluation depths | Depth | Layers | Confidence label | |---|---|---| | `quick` | static | Estimated | | `standard` (default for `score`) | static and judge | Assessed | | `deep` (used by `certify`) | static, judge, and Monte Carlo with 50 runs | Certified | | `thorough` | static, judge, and Monte Carlo with 100 runs | Certified+ | The label names the depth that ran, not a check against human judgment. A plugin directory gets the static layer only, whatever depth you ask for. ## Static layer (lint) …
Read the whole file at its exact version.
How to install
mdr add wshobson/agents/evaluation-methodology@sha256:d937b6d8c2a853bdThe line at the top of this page pins the label git:20260926.11f75d8, 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_rdhqyoqzgso55mn2)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Mar 25, 2026 and Sep 26, 2026, about one every 62 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260926.11f75d8 latest | 2026-09-26 | 11f75d8 | 7,908 B | A | view · diff |
| git:20260326.500ccf1 | 2026-03-26 | 500ccf1 | 22,160 B | A | view · diff |
| git:20260326.c3db094 | 2026-03-26 | c3db094 | 19,100 B | A | view · diff |
| git:20260325.b4afcc4 | 2026-03-25 | b4afcc4 | 1,768 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 (7908 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
wshobson/agents · 42,320 stars · license MIT · pushed 2026-11-08 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_rdhqyoqzgso55mn2 GET https://markdownregistry.com/api/v1/resolve?ref=wshobson/agents/evaluation-methodology GET https://markdownregistry.com/api/v1/blob/d937b6d8c2a853bdffd53ea5c900e8e650e372506d48b8f64808d82fb87014ee
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.