taste-sweep
Skill0 starsChanged 5 months agoMITView on GitHub
Sweep a whole codebase for design and prose taste, not one screen. Use when the user says "taste sweep", "taste-sweep", "audit the codebase for taste", "audit the repo for design", "where's the jank", or "find taste debt". Produces a ranked report of what to fix across the front-end and user-facing text. Read-only — applies no fixes. For a single screen or passage, use /taste-audit instead.
In this repository4 other files it gives its agents.
- taste-auditSkill
- taste-helpSkill
- taste-learnSkill
- tasteSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 11
Read the taste library at ~/.claude/taste/references.md (if it exists).
- Distinctive: line 16
Don't read every file. Find the surface, then sample what carries the most weight.
- Distinctive: line 22
Use Explore/Grep to locate.
- Distinctive: line 49
No fixes applied. Skip empty buckets.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Taste — sweep
Audit a whole codebase for taste. Find the patterns, not one-off nits. Report only.
Calibrate first
Read the taste library at ~/.claude/taste/references.md (if it exists). Judge
against the user's taste, not a generic ideal. A finding that fights a saved
reference loses.
Map the surface
Don't read every file. Find the surface, then sample what carries the most weight.
- Design system: tokens, theme, global CSS, the shared component library. Drift here multiplies everywhere — start here.
- High-traffic screens: entry points, the main flow, anything money- or auth-shaped.
- User-facing text: button labels, empty/error/success copy, headings, toasts, validation messages — grep the string surface. Use Explore/Grep to locate; for a large repo, fan out with subagents (or a workflow if the user opts in). Sample representative files; say what you sampled and skipped.
What to look for — patterns, ranked by blast radius
- Systemic jank: more than one typeface family; ad-hoc spacing/colors instead of tokens; inconsistent radius, shadow, or alignment; body text outside 15–25px / line-height 1.3–1.45 / 45–90 chars.
- Affordance rot: wrong control for the job repeated across screens; conventions broken by accident; inconsistent interactive states (hover/focus/disabled).
- Story gaps: missing empty/error/success states; hierarchy that buries the user's real question; flows with no arc.
- Prose clutter (Zinsser): copy thick with dead words and qualifiers; passive voice and weak verbs in UI text; jargon; stiff, voiceless microcopy.
Report
Open with a one-line verdict on the codebase's taste health. Then findings ranked by
blast radius — widest first — one line each: pattern, where it lives
(file:line or "across N components"), the fix. Group as:
- Systemic jank / clutter — fix first; one change, many screens.
- Affordance / clarity rot
- Story / voice gaps
- Polish Close with the single highest-leverage change and a rough count of what you didn't sample.
Rules
- Hunt repeated patterns; a one-screen nit belongs in /taste-audit, not here.
- Name the mechanism and the blast radius, not "feels off".
- No fixes applied. Skip empty buckets. Flag what you sampled vs skipped — silent truncation reads as "covered everything" when it didn't.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

