agent-eval-harness skillB
agent-eval-harness is agent-read markdown (skill) from onewave-ai/claude-skills: Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers..
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
# Agent Eval Harness Prompts are edited by vibe and shipped on hope. Then a model version changes and nobody finds out until a customer does. An eval set is the cheapest insurance in AI work: twenty cases, one script, run it every time anything changes. ## Core Behavior Build the smallest eval that would catch a real regression. Twenty cases you run every change beats two hundred you run once. ## Step 1 — Define Pass Before writing cases, write the pass condition. Vague quality goals produce vague evals. Good conditions are checkable: - Output is valid JSON matching this shape. - The answer contains the correct figure from the source document. - The refusal happens on these inputs and does not happen on those. - Tool `x` is called, with the customer id from the prompt. - No hallucinated field names outside the known schema. - Tone matches: no emojis, no corporate filler, under 120 words. ## Step 2 — Build the Set Pull cases from reality, not imagination. Real transcripts, real support tickets, real user prompts. Synthetic cases miss exactly the phrasing that breaks things. Cover four groups: | Group | Why | |-------|-----| | Happy path (~40%) | The thing it is for | …
Read the whole file at its exact version.
How to install
mdr add onewave-ai/claude-skills/agent-eval-harness@git:20260920.97b5147mdr add onewave-ai/claude-skills/agent-eval-harness@sha256:5b330171d63bd0a5Pin 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_kdltfxykmzdsdzqk)
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Versions
Audit of the latest version
- fail: No prompt-injection phrasing (matched: Ignore previous instructions)
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4221 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 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_kdltfxykmzdsdzqk GET https://markdownregistry.com/api/v1/resolve?ref=onewave-ai/claude-skills/agent-eval-harness GET https://markdownregistry.com/api/v1/blob/5b330171d63bd0a550e91d4386ddb31637f43e5a73255e33e2f779aef3b617e4
Your agent 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.