Data2Story

A data-journalist agent skill that turns any dataset into a verifiable, evidence-grounded multimodal story — a self-contained HTML article where every sentence traces back to the data or source that justifies it.

What it does

https://github.com/user-attachments/assets/7a2e2b65-3289-431d-b06a-230252df8774

Dataset → finished article. Point it at a CSV, a folder of data, or a paper, and a fixed pipeline of seven roles produces a publishable HTML story end to end.
Evidence-grounded. Every sentence and visual links back to its source. The pipeline emits a viewer.html inspector where you can click any claim to see the data, code, or citation behind it.
Multimodal by default. Charts, images, video, audio, maps, and interactive elements — chosen from the data's actual properties, not a fixed checklist. Media generation routes through OpenRouter.
Verifiable. Each run writes to its own versioned project folder and snapshots the exact skill versions used, so every result can be traced and re-checked.
Progressive disclosure. Each role's SKILL.md holds only its instructions; bulky reference material (output schemas, field rules, lookup tables) lives in that role's references/ folder as JSON and is loaded only when needed.

Two versions. The repository ships two peer skills under skills/ — the richer, current build is data2story-pro; the paper's reproducible version is data2story.

Skill Invoke What it is

data2story-pro /data2story-pro Improved version of data2story. See skills/data2story-pro/README.md.

data2story /data2story The paper's canonical 7-role pipeline.

Updates

[2026.6] Version 0.1.0: Optimized visual effects.
[2026.6.9] Released the arXiv paper, GitHub repository.
[2026.5.11] Data2Story was accepted as a Spotlight paper at the ACM Conference on AI and Agentic Systems workshop.

Installation & usage

Data2Story is an agent skill. The orchestrator lives in skills/data2story/SKILL.md — it works first-class with Claude Code, and equally with Codex, Cursor, Gemini CLI, and other agents.

Set your API key. Media generation routes through OpenRouter by default:
```
export OPENROUTER_API_KEY=sk-or-...
```
Run the skill on a dataset:
- Claude Code — make the skill available (place skills/data2story/ under ~/.claude/skills/, or run from inside this repo), then:
```
/data2story data/pick_a_card
```
- Codex / other agents — open the repo and ask the agent to follow the orchestrator:
```
Read skills/data2story/SKILL.md and run the Data2Story pipeline on data/pick_a_card
```
Open the output: index.html (the finished article) and viewer.html (the evidence inspector).

Project structure

data2story-skill/
├── skills/
│   ├── data2story/           the paper's canonical 7-role pipeline    ·  /data2story
│   ├── data2story-pro/       the extended 14-agent build              ·  /data2story-pro
│   │                         └ self-contained: its own README, package.json, example data/
│   ├── frontend-design/      visual design system used by data2story
│   ├── frontend-design-pro/  extended design system used by data2story-pro
│   ├── dataviz-craft/        chart-craft recipes               ·  data2story-pro helper
│   ├── find-data/            dataset discovery & validation    ·  data2story-pro helper
│   └── sparring-partner/     idea-to-topic ideation            ·  data2story-pro helper
├── .claude-plugin/           marketplace.json  ·  installs either skill
└── assets/                   shared images

Inside each orchestrator, a role is a SKILL.md + a references/ folder (JSON schemas & lookup tables) + any scripts/ it runs — e.g. designer/scripts/ (OpenRouter media tools), inspector/scripts/ (the verify.py / generate_viewer.py verifier), detective/scripts/ (media fetch helpers).

The virtual newsroom

Think of it as a small newsroom in a box. Each role reads what the previous one produced, then adds its own artifact — a fixed pipeline that runs once, end to end.

#	Role	What it does	Produces
1	Detective	Researches external context — domain background, history, why the data matters	`detective.json`
2	Analyst	Exhaustively profiles the data — distributions, correlations, trends, anomalies	`analyst.json`, `code/*.py`
3	Editor	Decides the narrative — what the article argues and which findings matter	`editor.md`, `editor.json`
4	Designer	Chooses how to show each point — charts, images, video, audio, interactives	`designer.json`, `assets/`
5	Programmer	Builds the final HTML, tagging every element with its source IDs	`index.html`
6	Auditor	Fixes layout issues — overlap, spacing, alignment — without changing content	`index.html` (fixed), `auditor.json`
7	Inspector	Verifies every sentence traces to its evidence; builds an interactive viewer	`inspector.json`, `viewer.html`

flowchart TB
    DATA[(dataset)]

    subgraph plan [Plan and design]
        direction LR
        DET[Detective] -->|detective.json| ANA[Analyst]
        ANA -->|analyst.json + code| EDT[Editor]
        EDT -->|editor.md + editor.json| DES[Designer]
    end

    subgraph build [Build and verify]
        direction LR
        PRG[Programmer] -->|index.html| AUD[Auditor]
        AUD -->|index.html| INS[Inspector]
    end

    DATA --> DET
    DES -->|designer.json + assets| PRG
    INS -->|inspector.json + viewer.html| OUT([article + evidence viewer])

License

Released under the MIT License.

Acknowledgement

If you use Data2Story in your research, please kindly cite:

@article{data2story,
  title   = {Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories},
  author  = {Lin, Kevin Qinghong and EI, Batu and Shi, Yuhong and Lu, Pan and Torr, Philip and Zou, James},
  journal = {arXiv preprint arXiv:2606.11176},
  year    = {2026}
}

Data2story Skill

README