uig SKILL.md skillA
uig 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/uig@git:20261003.9a39ab5Pins git:20261003.9a39ab5 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/uig/SKILL.md- Versions recorded
- 1
- Latest version
- git:20261003.9a39ab5, committed Oct 3, 2026
- Size
- 15,109 bytes
- Repository stars
- 94
- License
- MIT
Build a User Input Grid (UIG) for an AI product or feature, evaluate existing eval datasets against it, and propose new inputs to fill coverage gaps. Use this skill whenever someone asks to design an eval framework, audit a test set, build a "user input grid", "synthetic query matrix" or "SQM", improve dataset coverage, or assess whether their offline evals reflect what real users will actually send. Also trigger when they share a product domain + sample dataset and want to know what the…
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
# User Input Grid Skill A User Input Grid (UIG) — also called a Synthetic Query Matrix (SQM) — is a structured framework for ensuring eval coverage of an AI product reflects the real diversity of users, content domains, input types, and input styles the system will face in production. It comes from the Reforge AI Evals curriculum and a few teams at Amplitude, Linear, and Notion have published versions of it. The core idea: pick 3–5 dimensions that drive meaningful diversity in your product, define 4–7 values per dimension, and treat the cartesian product (pruned for plausibility) as your eval sourcing matrix. A 4-dimension grid with average ~5 values per dimension gives ~625 theoretical combinations — practical eval sets land at 30–80 high-coverage inputs after pruning. The reason this matters: most AI eval datasets are built from one of three weak sources — engineer intuition (overfits to features the engineer knows about), real-user logs (overfits to common easy cases users actually try), or synthetic generation without a framework (random uneven coverage). A UIG forces you to be deliberate about *what* you're testing, makes gaps visible, and …
Read the whole file at its exact version.
How to install
mdr add calibre-labs/reforge-ai-evals/uig@sha256:2cb7b332a5dea456The line at the top of this page pins the label git:20261003.9a39ab5, 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_ujyseoyrujrzarhe)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Oct 3, 2026.
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 (15109 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_ujyseoyrujrzarhe GET https://markdownregistry.com/api/v1/resolve?ref=calibre-labs/reforge-ai-evals/uig GET https://markdownregistry.com/api/v1/blob/2cb7b332a5dea4565180af749787586bc8c41e42880b9d93f49ba5e8175a3b78
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.