Review a finished Data2Story blog against the 5 quality rubric dimensions (visual_design, narrative_pacing, data_method_transparency, claim_data_alignment, insight_value), score each 1-7 with on-page evidence, and emit critic.json with pass/fail + targeted, surgical send-back instructions. Verifies every load-bearing claim/asset against its traceability chain before scoring; applies the caveat-survival, honest-accuracy, and third-party-attribution caps. Does NOT rewrite content — scores and sends back. Use at Stage 6.5 after the Auditor and after verify.py has produced verifier.json; re-runs each revision round. Triggers: a built index.html plus verifier.json exist, or you need to judge whether the article is actually good.
How to install critic?
qinghonglin/data2story-skill/critic
$npx -y skills add qinghonglin/data2story-skill --skill criticInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/qinghonglin/data2story-skill" --skill "qinghonglin/data2story-skill/critic"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/qinghonglin/data2story-skill" that are relevant to the current task. Run `npx skills add "https://github.com/qinghonglin/data2story-skill"` and select the relevant skills, then follow their instructions.
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