Skill

Auto data profiler + AI narrative generator. Upload CSV/Excel → get an executive report. Built as a Claude Skill.

Install

npx -y skills add dinesh0666/data-story --skill skill

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Auto-generates an executive data narrative report from any uploaded CSV or Excel file. Use this skill whenever a user uploads a CSV, XLSX, or data file and wants analysis, a data story, a data profile, a summary report, insights, anomaly detection, or an executive summary of their data. Also trigger when user says things like "analyze this data", "what does this dataset say", "generate a report from this file", "profile my data", "summarize this spreadsheet", "turn this into a story", or "data story". The output is a polished Word document (.docx) with a full data profile, key metrics, anomaly callouts, trend insights, and an AI-written executive narrative — zero manual effort.

SKILL.md

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DataStory — Auto Data Profiler + Narrative Generator

Given any CSV or Excel file, this skill profiles the data, generates an AI narrative via the Anthropic API, and outputs a polished .docx executive report. No manual analysis required.

Scripts

Script	Purpose
`scripts/profile_data.py`	Profiles a CSV/XLSX file → outputs JSON stats
`scripts/generate_report.js`	Takes profile + narrative JSON → outputs `.docx`
`scripts/run_datastory.sh`	Full orchestrator: profile → narrative → docx

Quick Run (full pipeline)

export ANTHROPIC_API_KEY=sk-ant-...
bash scripts/run_datastory.sh mydata.csv
# Output: datastory_mydata.docx

Step-by-step workflow

Step 1 — Profile the data

python3 scripts/profile_data.py <filepath> [--max-rows 10000] > profile.json

Outputs JSON with:

shape — rows x columns
missing_summary — total missing cells and %
columns[] — per-column: dtype, null %, unique count, and either numeric stats or top_values or datetime range
sample_rows — first 5 rows

Edge cases:

Files >10k rows are sampled automatically
CSV encoding failures fall back to latin-1

Step 2 — Generate narrative via Anthropic API

Call claude-sonnet-4-20250514 with max_tokens: 4000.

System prompt: instruct the model to return ONLY JSON with keys: executive_summary, dataset_overview, key_findings (array of 5), anomalies (array), column_insights (array of {column, insight}), data_quality_score (int 0-100), data_quality_label (Poor/Fair/Good/Excellent), data_quality_assessment, recommended_next_steps (array of 3).

Slim the profile before sending: keep only 3 sample rows and 3 top_values per column. Parse: strip markdown fences, JSON.parse. On failure, extract first {...} block with regex.

Step 3 — Generate .docx report

node scripts/generate_report.js payload.json [output.docx]

payload.json format: { "profile": {...}, "narrative": {...}, "filename": "myfile.csv" }

Report sections:

Cover — title, filename, date
Executive Summary — callout box + dataset overview
Dataset Overview — stats table
Key Findings — numbered list
Anomalies & Concerns — amber callout (skipped if empty)
Column Profiles — full table with name, type, nulls, stats, outliers
Column Insights — bulleted insights
Data Quality Assessment — score + paragraph
Recommended Next Steps — numbered list
Appendix: Sample Data — first 5 rows

docx rules: WidthType.DXA only, dual widths on tables, ShadingType.CLEAR, no unicode bullets, no backslash-n in text, outlineLevel on headings for TOC.

Step 4 — Deliver

Copy to /mnt/user-data/outputs/ and call present_files. Name: datastory_<original_filename_without_extension>.docx

Error handling

Situation	Action
ANTHROPIC_API_KEY not set	Skip narrative, insert placeholder text
pandas missing	Auto-install via pip
docx npm package missing	Auto-install via npm
JSON parse failure	Strip fences, extract first {...} block
File >100k rows	Sample 10k rows

React Artifact

../app/DataStory.jsx runs this entire pipeline in-browser via the Anthropic API (Claude-in-Claude pattern). Upload a file, get a full interactive report instantly.