distribution-profiler skillA
distribution-profiler is agent-read markdown (skill) from ai-analyst-lab/ai-analyst: Single-column distribution deep-dive. Profile the statistical distribution of a data column and produce an analytical playbook: distribution identification, valid summary stats, recommended tests, A/B guidance, traps. Trigger on "profile this column", "what distribution is this", "check the distribution", "is this normal", "what test should I use", "check assumptions before A/B test", "how is this data distributed"..
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: Distribution Profiler ## Purpose Take any numeric data column and produce a complete analytical playbook: identify the distribution, compute the right summary statistics, recommend the correct statistical tests, flag common traps, and give specific A/B testing guidance. This skill exists because the #1 mistake in product analytics is assuming data is normal when it's not — leading to wrong tests, false positives, and misleading dashboards. The profiler catches this automatically. ## When to Use - Before any analysis involving a numeric metric - When the user asks "what distribution is this?" or "what test should I use?" - When checking assumptions for an A/B test - When a user says "profile" or "understand" a metric - Proactively when you notice an analysis is about to use a t-test or OLS on data that hasn't been checked ## Invocation `/distribution-profiler` — profile a data column's distribution ## Instructions ### Step 0: Identify the Target Figure out what column/metric the user wants profiled. This could be: - A specific column name (e.g., "total_amount from orders") - A derived metric (e.g., "revenue per user", "sessions per user per month") …
Read the whole file at its exact version.
How to install
mdr add ai-analyst-lab/ai-analyst/distribution-profiler@git:20260902.b370de6mdr add ai-analyst-lab/ai-analyst/distribution-profiler@sha256:a0bc37ab347f404bPin 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_oqtx5p2d67csu7dd)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260902.b370de6 latest | 2026-09-02 | b370de6 | 9,539 B | A | view · diff |
| git:20260827.7ff2e25 | 2026-08-27 | 7ff2e25 | 9,568 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 (9539 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_oqtx5p2d67csu7dd GET https://markdownregistry.com/api/v1/resolve?ref=ai-analyst-lab/ai-analyst/distribution-profiler GET https://markdownregistry.com/api/v1/blob/a0bc37ab347f404b8e58d0e4873a8241313c4da93d37398507a0f173fce154f4
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