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.

• 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.

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.

1. Set your API key. Media generation routes through OpenRouter by default:

   export OPENROUTER_API_KEY=sk-or-...

2. 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
     

3. Open the output: index.html (the finished article) and viewer.html (the evidence inspector).

data2story-skill/
├── skills/
│   ├── data2story/        the agent: SKILL.md (orchestrator) + one folder per role
│   │                      each role = SKILL.md + references/ (JSON) + scripts/ (the tools it runs)
│   │                        · designer/scripts/  — OpenRouter media tools (text→image/video/music, embeddings)
│   │                        · inspector/scripts/ — verify.py + generate_viewer.py
│   │                        · detective/scripts/ — Wikimedia/Commons fetch helpers
│   └── frontend-design/   shared UI/visual design system the Designer & Programmer borrow from
├── data/     example datasets
└── assets/   shared images

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.

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])

Released under the MIT License.

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}
}