jev-integrate skillA
jev-integrate is agent-read markdown (skill) from onewave-ai/claude-skills: Wire a System One model (Jev, or an open reproduction like Von) into a product feature — routing, guardrails, scoring, classification. Use when replacing an LLM call that returns a label rather than prose, when adding a typed decision to an agent loop, or when deciding between the hosted Jev API and a local open model. Covers question design, the eval-set-first workflow, threshold calibration, confidence gates, and the traps measured on real data..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Wiring a System One model into a feature A System One model answers **typed questions in one forward pass**. It generates no text. State in, typed answers with calibrated probabilities out. It is an if-statement that can read. Use it when the decision is **narrow, pre-specified, and repeated**. Do not use it for anything that needs a written explanation — that is still a job for Claude. ## Before anything else: is this actually the right tool Answer these three. If any is "no", stop and keep the LLM call. 1. **Are the possible answers known up front?** Choice caps at 255 options. 2. **Does the caller need only the label**, not the reasoning? If a human reads a justification downstream, you need prose and this is the wrong tool. 3. **Is it high volume, or is a person waiting?** This is a latency and cost optimisation, not a capability gain. It knows nothing Claude doesn't. On a nightly cron over fifty records it buys you a dependency and nothing else. Measured on 150 hand-labelled records across three jobs (our Sep 20 2026 run): Jev ties GPT-5.2 at **145/150** and costs **46x less** ($0.036 vs …
Read the whole file at its exact version.
How to install
mdr add onewave-ai/claude-skills/jev-integrate@git:20260923.352d573mdr add onewave-ai/claude-skills/jev-integrate@sha256:36e44fbdca47604cPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_pdacmqk5pr5zxlpk)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260923.352d573 latest | 2026-09-23 | 352d573 | 7,750 B | A | view · diff |
| git:20260921.1fa6175 | 2026-09-21 | 1fa6175 | 6,731 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 (7750 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 · 306 stars · license MIT · pushed 2026-09-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_pdacmqk5pr5zxlpk GET https://markdownregistry.com/api/v1/resolve?ref=onewave-ai/claude-skills/jev-integrate GET https://markdownregistry.com/api/v1/blob/36e44fbdca47604c4860c494e30339e82b72640ebade4935c681da5c7de26f6f
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