srm-check skillA
srm-check is agent-read markdown (skill) from ai-analyst-lab/ai-analyst: Automatically detect Sample Ratio Mismatch (SRM) in experiment or A/B test data before any analysis proceeds. SRM is a critical randomization integrity check — if the treatment/control split deviates significantly from the expected ratio, the experiment is compromised and results cannot be trusted. This skill acts as a safety gate that blocks analysis when randomization is broken. Use this skill whenever you detect experiment or A/B test data — look for columns like "variant", "group", "treatme.
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
# Skill: SRM Check (Sample Ratio Mismatch) ## Purpose Automatically detect Sample Ratio Mismatch in experiment data before any analysis proceeds. SRM is a randomization integrity check — if the treatment/control split deviates significantly from the expected ratio, the experiment is compromised and results cannot be trusted. This skill acts as a safety gate that blocks analysis when randomization is broken. ## When to Use Apply this skill when: 1. **Loading any experiment or A/B test dataset** — auto-fire on detection of treatment/control columns (e.g., `variant`, `group`, `treatment`, `arm`, `experiment_group`) 2. **Before any treatment effect calculation** — SRM must pass before comparing outcomes 3. **When the Experiment Analyzer agent starts** — first step of any experiment analysis workflow This skill auto-fires on experiment data detection. Do NOT wait to be asked. ## Instructions ### What Is SRM? …
Read the whole file at its exact version.
How to install
mdr add ai-analyst-lab/ai-analyst/srm-check@git:20260902.b370de6mdr add ai-analyst-lab/ai-analyst/srm-check@sha256:8cc05c00dec437ddPin 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_k5fuky57lggzcb3n)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260902.b370de6 latest | 2026-09-02 | b370de6 | 9,012 B | A | view · diff |
| git:20260827.7ff2e25 | 2026-08-27 | 7ff2e25 | 9,507 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 (9012 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
ai-analyst-lab/ai-analyst · 302 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_k5fuky57lggzcb3n GET https://markdownregistry.com/api/v1/resolve?ref=ai-analyst-lab/ai-analyst/srm-check GET https://markdownregistry.com/api/v1/blob/8cc05c00dec437dde61ae95da302d99d523bd95abfc1f9b986a4d296c619c57f
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