// Use when first encountering a new dataset — produces a structured profile (schema, missingness, distributions, outliers, gotchas) before any analysis.
| name | dataset-profiler |
| description | Use when first encountering a new dataset — produces a structured profile (schema, missingness, distributions, outliers, gotchas) before any analysis. |
| version | 0.1.0 |
| status | experimental |
| risk | low |
| tags | ["data","read-only","writes-files"] |
| Name | Type | Required | Notes |
|---|---|---|---|
path | path | yes | CSV / Parquet / JSONL |
target | string | no | column of interest (gets extra distribution detail) |
profile.md with: Source, Schema, Missingness, Distributions, Outliers, Joins / keys, Gotchas, Open questions.
-1, 9999-12-31)Use when capturing an architecture decision so it survives turnover — produces an ADR-NNNN.md from context, options considered, and the chosen path.
Use when reviewing a proposed REST or GraphQL API change before merge — checks contract clarity, backwards compatibility, errors, pagination, auth, and naming.
Use after an incident is resolved — drafts a blameless postmortem from timeline notes, alerts, and chat threads.
Use when opening a PR — produces a clean PR description (what / why / how to verify / risks) from a branch diff against base.
Use when planning the next sprint — turns ticket intake + team capacity into a planned sprint with explicit non-goals.
Use after a session to promote useful episodic notes from logs/episodic/ into distilled, dated entries in MEMORY.md and memory/semantic/.