eval-code SKILL.md skillA
eval-code from calibre-labs/reforge-ai-evals is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add calibre-labs/reforge-ai-evals/eval-code@git:20261102.9ec9f47Pins git:20261102.9ec9f47 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- calibre-labs/reforge-ai-evals
- Path
skills/eval-code/SKILL.md- Versions recorded
- 2
- Latest version
- git:20261102.9ec9f47, committed Nov 2, 2026
- First version recorded
- Oct 3, 2026
- Size
- 11,307 bytes
- Repository stars
- 94
- License
- MIT
Write deterministic, code-based evaluator functions for an AI product. Use this skill whenever you need to write evaluators that check structural properties of AI outputs (format, count, presence, schema compliance) without calling another LLM. Also use when auditing existing code-based evaluators for brittleness, coverage gaps, or false positives.
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
# Code-Based Evaluator Skill Code-based evaluators are deterministic functions that check AI outputs using regex, string operations, schema validation, or simple parsing — no LLM call required. They are fast, cheap, and produce the same result every time, which makes them the foundation of any eval suite. The tradeoff: they can only check what is mechanically verifiable. They cannot assess whether the content is *correct*, *relevant*, or *well-reasoned*. Use them for structural properties; use LLM judges for semantic ones. ## When to use this skill Write code-based evaluators when the property you want to check can be expressed as: - **Presence/absence**: does the output contain X? (a section heading, a citation, a table) - **Count**: does the output contain exactly/at least N of something? (3 companies, 3 sources) - **Format compliance**: is the output in the expected structure? (JSON schema, markdown table) - **Value range**: is a number within expected bounds? (confidence score 0–1, year 1900–2030) - **String match**: does the output contain a required string? (company name, required disclaimer) Do NOT write a code-based evaluator for: …
Read the whole file at its exact version.
How to install
mdr add calibre-labs/reforge-ai-evals/eval-code@sha256:ac6d2518d2641917The line at the top of this page pins the label git:20261102.9ec9f47, 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_wtswwnfa7wwxollt)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Oct 3, 2026 and Nov 2, 2026, about one every 31 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261102.9ec9f47 latest | 2026-11-02 | 9ec9f47 | 11,307 B | A | view · diff |
| git:20261003.9a39ab5 | 2026-10-03 | 9a39ab5 | 8,503 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 (11307 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
calibre-labs/reforge-ai-evals · 94 stars · license MIT · pushed 2026-11-05 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_wtswwnfa7wwxollt GET https://markdownregistry.com/api/v1/resolve?ref=calibre-labs/reforge-ai-evals/eval-code GET https://markdownregistry.com/api/v1/blob/ac6d2518d2641917c72b0f0ffc7a1a7fdcae9e6af6665f05d57a58241e32ae1e
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.