jev-eval SKILL.md skillA
jev-eval from onewave-ai/claude-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add onewave-ai/claude-skills/jev-eval@git:20260923.352d573Pins git:20260923.352d573 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- onewave-ai/claude-skills
- Path
jev-eval/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260923.352d573, committed Sep 23, 2026
- First version recorded
- Sep 21, 2026
- Size
- 6,572 bytes
- Repository stars
- 421
- License
- MIT
Build and run a labelled eval set for a System One model (Jev, Von, or any typed-decision config), then sweep criteria wordings and thresholds against it. Use when a Jev/Von classification is wrong or unreliable, when choosing between the hosted API and a local open model, when tuning noul thresholds, or before shipping any typed-decision feature. Produces an accuracy-by-wording matrix and a calibrated threshold.
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
# Evaluating a typed-decision config
**The eval set is the product.** A System One model's accuracy is dominated by how the
question was written, and the failure mode is silent — it returns a confident, type-valid,
wrong answer. Without labels you cannot tell a bad question from a bad model.
Measured: rewriting the criteria moved an open model from **4/15 to 14/15** on 15 records.
No model change. Then the same comparison at 150 records put that model at **61%** overall
against Jev's **97%** — the 15-record read was an artifact of a small, easy set. Both facts
are the point: wording swings results, and small sets lie about which way.
## Run it
```bash
python ~/.claude/skills/jev-eval/scripts/sweep.py labelled.json configs.json \
--backend jev|von --question <name>
```
`labelled.json` is `[{"id","state","truth"}]`. `configs.json` maps a config name to
`{"instructions", "criteria"}` — a dict of options makes it a **choice**, a list of levels
makes it a **score**, omitting it makes it a **noul**. The script reads the Jev key from
Keychain (`typesafe-api-key`), prints accuracy per config, labels the spread
…Read the whole file at its exact version.
How to install
mdr add onewave-ai/claude-skills/jev-eval@sha256:c2f7fe3f473e83d1The line at the top of this page pins the label git:20260923.352d573, 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_qkspczuhkor63vwg)
6 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Sep 21, 2026 and Sep 23, 2026, about one every 2 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260923.352d573 latest | 2026-09-23 | 352d573 | 6,572 B | A | view · diff |
| git:20260921.1fa6175 | 2026-09-21 | 1fa6175 | 5,441 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 (6572 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
onewave-ai/claude-skills · 421 stars · license MIT · pushed 2026-10-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_qkspczuhkor63vwg GET https://markdownregistry.com/api/v1/resolve?ref=onewave-ai/claude-skills/jev-eval GET https://markdownregistry.com/api/v1/blob/c2f7fe3f473e83d1c8274ce754a5c5ae6fedb3a076787c3537c3645b5f17143a
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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