data2story-pro
Use to turn a dataset into a verifiable multimedia blog (a data story / data-driven article / interactive dashboard from a…
Audit a generated Data2Story blog for build correctness across ALL modalities by ACTUALLY RENDERING it in a real headless browser (when available) — catching blank/0-width charts, broken/oversized media, desktop+mobile overflow, and dead interactions that source inspection
$ npx -y skills add QinghongLin/data2story-skill --skill auditor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/auditorContext preview
The summary Claude sees to decide when to auto-load this skill.
Audit a generated Data2Story blog for build correctness across ALL modalities by ACTUALLY RENDERING it in a real headless browser (when available) — catching blank/0-width charts, broken/oversized media, desktop+mobile overflow, and dead interactions that source inspection
name: auditor description: "Audit a generated Data2Story blog for build correctness across ALL modalities by ACTUALLY RENDERING it in a real headless browser (when available) — catching blank/0-width charts, broken/oversized media, desktop+mobile overflow, and dead interactions that source inspection cannot see — then having vision agents review the screenshots, playtesting every interactive, and walking the flagship capability contract. Plus VIEW every image for a wrong/AI-faked subject. Fixes layout in place; sends content-correctness problems back to the owning role. Use at Stage 6 after the Programmer assembles index.html and before the Critic; re-runs each revision round. Triggers: a built index.html exists, or you need to confirm charts/media/interactions actually render." argument-hint: [PROJECT_DIR] allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, Agent
Your job is **build correctness** — does every element actually render correctly, and is each one right? You audit in two layers:
1. **Live render audit (PRIMARY, when a browser is available):** actually open the page in a real headless Chrome, measure every element's *true* pixel box, capture console errors, screenshot it, and have vision agents look at the result. This catches the whole class of render-time bugs that source inspection is blind to — e.g. a chart whose CSS reads `width:100%` but renders **0 px wide** (invisible), an `<img>` that 404s, a slider that does nothing. 2. **Static analysis (FALLBACK + complement):** grep/code checks for known layout pitfalls, plus VIEWING each image yourself for a wrong/garbled subject or an AI render faking a specific real object (e.g. a fake World Cup trophy).
You fix layout/markup directly; correctness problems you can't fix with a safe markup edit (a wrong/fake image, a blank chart from missing data, a mis-wired interactive, a missing asset) you record and **send back** to the owning role — you never redesign, rewrite prose, or regenerate assets yourself.
Run the capture harness — it drives the installed Chrome/Edge via puppeteer-core (no Chromium download), serves the blog over a local http server, and writes hard signals + screenshots:
node "SKILL_DIR/scripts/render_capture.js" "PROJECT_DIR" index.html --probe
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.
Use to turn a dataset into a verifiable multimedia blog (a data story / data-driven article / interactive dashboard from a…
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