assess-graphical-excellence
assess-graphical-excellence is a Scientific data analysis & plotting skill for AI agents, published by gnurio in the tufte-vdqi-plugin repository on GitHub. Skillspace rates assess-graphical-excellence B (81/100) and it passed the safety scan; the rating is based on static analysis only.
Evaluate a data graphic against Edward Tufte's nine criteria, name the chartjunk species present, compute lie factor, compare against VDQI's named-failure catalogue, and return prioritised fixes tagged with the specific Tufte remedy (B1–B7), genre to switch to (C1–C10), and exemplar to emulate. Use whenever someone asks whether a chart is good, what is wrong with a chart, how to clean up or declutter a chart, whether a graphic is misleading, or for any Tufte-style critique of an existing visualization.
- Grade
- B
- Quality
- 81 / 100
- Safety
- Passed
- GitHub stars
- 267
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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