eval-models SKILL.md skillA
eval-models from abhiindigloo/evalharness is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add abhiindigloo/evalharness/eval-models@git:20261103.c0363cfPins git:20261103.c0363cf in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- abhiindigloo/evalharness
- Path
skills/eval-models/SKILL.md- Versions recorded
- 3
- Latest version
- git:20261103.c0363cf, committed Nov 3, 2026
- First version recorded
- Oct 14, 2026
- Size
- 6,507 bytes
- Repository stars
- 7
- License
- MIT
Run the user's own examples against several AI models (Claude, Gemini, OpenAI, or any OpenAI-compatible endpoint including local Ollama or vLLM) and measure pass rate, latency, and billed cost to find the cheapest model that meets their quality bar. Use whenever the user wants to test, benchmark, evaluate, or prove which model works for their task, asks "is the cheaper model good enough", wants evidence before switching models, or has a shortlist from find-model to validate, or wants evals…
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
# Evaluate models on the user's examples Turn a model recommendation into evidence. The script sends identical prompts to each candidate, applies deterministic checks to every reply, and reports pass rate, latency, tokens, and cost. It uses only the Python 3.9+ standard library. ## Workflow 1. **Agree the candidates.** Use the shortlist from find-model or the user's list. Each needs the exact current model ID and route; verify IDs from official docs. Read references/config-schema.md for the fields and supported providers. 2. **Collect examples.** Ask for 10 to 30 representative inputs, including hard and edge cases. They should be redacted or synthetic. Fewer than 10 examples is a smoke test; say so. In a repository, draft them first: call the `modelfinder_draft_eval_examples` MCP tool (or run `python3 scripts/repo_scan.py examples .`). It reads prompt files and fixtures (`prompts/`, `evals/`, `fixtures/`, `*.prompt.md`, JSONL with `input`, `prompt` or chat `messages`), drops any candidate containing detected personal data or secrets, and returns drafts with empty `checks`. Show the drafts to the user, let them remove or edit any, fill template variables, and agree checks… …
Read the whole file at its exact version.
How to install
mdr add abhiindigloo/evalharness/eval-models@sha256:1df1023c91338911The line at the top of this page pins the label git:20261103.c0363cf, 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_kkuhajhe5fxwk4ff)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 3 versions of this file, between Oct 14, 2026 and Nov 3, 2026, about one every 10 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261103.c0363cf latest | 2026-11-03 | c0363cf | 6,507 B | A | view · diff |
| git:20261016.b34e048 | 2026-10-16 | b34e048 | 6,371 B | A | view · diff |
| git:20261014.4490b68 | 2026-10-14 | 4490b68 | 5,077 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 (6507 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
abhiindigloo/evalharness · 7 stars · license MIT · pushed 2026-11-04 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_kkuhajhe5fxwk4ff GET https://markdownregistry.com/api/v1/resolve?ref=abhiindigloo/evalharness/eval-models GET https://markdownregistry.com/api/v1/blob/1df1023c9133891123d3999df44797cc803f19f8c989ec65ce168be54ad122ce
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.