SPB Git

spb/ultra-sharp-agent-skills Public

Ultra-Sharp Agent Skills — a research-first skill-authoring system + 72 production-ready skills for AI agents.

Python 100%
1.9 KB · 53 lines markdown
Rendered Raw Blame History
1<!--2Author: Simon-Pierre Boucher3Contact: contact@spboucher.ai4-->56# Report Format — CSV Data-Quality Profile78Render the profiler's JSON into exactly this Markdown structure. Do not add,9remove, or reorder sections.1011```markdown12# Data Profile: <file name>1314**Verdict:** <one of the three verdict lines below>1516## Overview17| Metric | Value |18|---|---|19| Rows profiled | <rows> (+ " (truncated at 100,000)" if truncated) |20| Columns | <number of columns> |21| Duplicate rows | <duplicate_rows> |22| Ragged rows | <ragged_rows> |2324## Columns25| Column | Type | Nulls | Unique | Stats |26|---|---|---|---|---|27| <name> | <type> | <nulls> | <unique> | <stats cell — see rule below> |2829## Issues30- <one bullet per detected issue; write "None detected." if empty>31```3233## Cell and verdict rules3435**Stats cell:**36- numeric columns → `min=<min>, max=<max>, mean=<mean>, median=<median>` plus `, outliers=<n>` when the key is present and > 037- string columns → `top: <value> (<count>), <value> (<count>), ...` from `top_values`38- boolean/date/empty columns → `—`3940**Issue bullets** (include each only when its condition is true):41- `nulls > 0` in a column → "`<column>` has <n> missing values (<percent of rows>%)"42- `duplicate_rows > 0` → "<n> duplicate rows"43- `ragged_rows > 0` → "<n> rows have an inconsistent number of fields"44- `outliers` present and > 0 → "`<column>` has <n> outliers (>3σ from mean)"45- `encoding_fallback` is true → "file is not valid UTF-8; profiled using latin-1 fallback"46- `truncated` is true → "profile limited to the first 100,000 rows"47- `rows == 0` → "file contains no data rows"4849**Verdict line** (pick exactly one, in this priority order):501. `rows == 0` OR `ragged_rows > 0``⚠️ Needs attention — <short reason>`512. any other issue bullet present → `🟡 Usable with caveats — <n> issue(s) found`523. no issue bullets → `✅ Clean — no data-quality issues detected`53