inspector
Run sentence-level traceability verification on a Data2Story blog (verify.py -> verifier.json), then emit the in-page Inspector panel (the reader-facing runnable verifier) + the verify/ artifacts (verify_map.json, run_cells.json, the reproducible notebook, cell_registry.json). Mostly Python; the runnable layer recomputes each computation in-browser from its inlined data and grades it against the published output, while the bundled notebook re-executes from raw data. Use verify.py at Stage 6.4 (after validate.py, before the Critic) and generate_viewer.py at Stage 7 after the Programmer authors
npx skills add QinghongLin/data2story-skill --skill inspector --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Inspector Your job is **traceability verification** plus standing up the **runnable verify layer** — a reader can recompute each computation in-browser (from its inlined data), and the bundled notebook re-executes the headline numbers from raw data (that notebook is the paper's coding verifier). You parse the blog HTML, link each visible sentence back to its evidence in the role JSONs (`verify.py → verifier.json`), and then build the **in-page Inspector panel**: a click-any-claim drawer embedded in `index.html` whose evidence is byte-identical to the on-disk `verify/` artifacts, backed by a reproducible notebook that re-runs the headline numbers from raw data. **This whole layer is MANDATORY on every blog.** A blog without a working Inspector panel, the `verify/` artifacts, and a clean reproducible notebook is incomplete. ## Setup - `PROJECT_DIR` = first argument - Resolve `SKILL_DIR` = the directory containing this `SKILL.md` (`.../skills/data2story-pro/inspector`). Replace `SKILL_DIR` placeholders with the resolved, quoted path before running Bash. Do not hard-code machine-local paths. - Required files in PROJECT_DIR: `index.html`, `analyst.json`, `detective.json`, `designer.js
- Setup
- Step 1: Run verify.py (sentence → evidence map) — early, at Stage 6.4
- Step 2: Emit the Inspector panel + verify/ artifacts
- Kinds the panel renders
- Byte-identical inline rule (hard)
- data- contract (no new attribute)
- Scripts
- Running the steps
- Output
python3 SKILL_DIR/scripts/verify.py PROJECT_DIR python3 SKILL_DIR/scripts/generate_viewer.py PROJECT_DIR
What does the inspector skill do?
Run sentence-level traceability verification on a Data2Story blog (verify.py -> verifier.json), then emit the in-page Inspector panel (the reader-facing runnable verifier) + the verify/ artifacts (verify_map.json, run_cells.json, the reproducible notebook, cell_registry.json). Mostly Python; the runnable layer recomputes each computation in-browser from its inlined data and grades it against the published output, while the bundled notebook re-executes from raw data. Use verify.py at Stage 6.4 (after validate.py, before the Critic) and generate_viewer.py at Stage 7 after the Programmer authors
How do I install it?
Run `npx skills add QinghongLin/data2story-skill --skill inspector --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From QinghongLin/data2story-skill, a repository with 149 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.