# Spreadsheet Signal Brief

> Analyze an attached CSV or Excel XLSX file and produce an evidence-backed data quality, range, duplicate, missing-value, and anomaly brief.

- Skill: `skygazer42/spreadsheet-signal-brief` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add skygazer42/spreadsheet-signal-brief`
- Raw SKILL.md: https://api.skillmd.com/api/skills/skygazer42/spreadsheet-signal-brief/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- License: Apache-2.0
- Author: skygazer42 (https://skillmd.com/u/skygazer42)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/skygazer42/spreadsheet-signal-brief

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# Spreadsheet Signal Brief

Analyze CSV or XLSX data supplied by the user and produce a compact decision brief.

## Procedure

1. If no CSV or XLSX attachment is available, ask the user to attach one. Do not invent a dataset.
2. Run `python3 scripts/analyze_spreadsheet.py "<sandbox_path>" --output /workspace/artifacts/data_quality_report.md` from this Skill directory, using the attachment's declared `sandbox_path` exactly.
3. Do not install packages or rewrite the parser; the bundled script uses only Python's standard library.
4. Read the generated report and distinguish observed aggregates from interpretations.
5. Avoid reproducing sensitive row-level values. Quote only column names and aggregate values that support each finding.

## Response format

- Overview
- Data quality
- Key signals
- Caveats
- Suggested next steps

Return `data_quality_report.md` as the output artifact. For small or incomplete datasets, state the limitation prominently. Never imply causation from correlation alone.