# Datastory

> 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: `dinesh0666/datastory` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds@latest add dinesh0666/datastory`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dinesh0666/datastory/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: dinesh0666 (https://skillmd.com/u/dinesh0666)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/dinesh0666/datastory

---


# 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)

```bash
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

```bash
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

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

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

Report sections:
1. Cover — title, filename, date
2. Executive Summary — callout box + dataset overview
3. Dataset Overview — stats table
4. Key Findings — numbered list
5. Anomalies & Concerns — amber callout (skipped if empty)
6. Column Profiles — full table with name, type, nulls, stats, outliers
7. Column Insights — bulleted insights
8. Data Quality Assessment — score + paragraph
9. Recommended Next Steps — numbered list
10. 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.