agentleFS
DROOdotFOODROOdotFOO/agent-skills/skills/frontend-slop-audit/SKILL.md

frontend-slop-audit

Skill1 starsChanged 2 months agoMITView on GitHub

Audit generated web UI for AI-generated tells and ship-blocking layout defects. TRIGGER when: reviewing a landing page, portfolio, or marketing site before shipping; user asks why a page "looks AI-generated", "looks templated", or "looks generic"; or asks for an anti-slop pass, taste pass, or pre-flight check on frontend output. DO NOT TRIGGER when: making design-system decisions such as tokens, palettes, type scales, or motion architecture (use design-ux skill), reviewing code correctness or security (use code-review skill), generating favicons or social images (use web-asset-generator skill), working on terminal/TUI interfaces (use design-ux skill), or fixing the flagged page rather than auditing it (use impeccable skill if installed, else design-ux skill).

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Countable before subjective: run the mechanical checks first.

    line 81
  2. Distinctive:

    Empirical, not eternal: every tell carries a date stamp and an expiry expectation

    line 83

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

frontend-slop-audit

Audit an already-built page for the patterns that mark it as machine-generated. This is a review pass, not a design pass: it takes existing output and returns a list of specific, located defects.

Two kinds of finding. Hard rules are countable or measurable -- a wrapped CTA, a two-line nav, five eyebrows across seven sections -- and failing one means the page is broken, not merely unfashionable. Tells are patterns that are individually defensible but appear so reliably in generated output that their presence identifies the author. Both are empirical, mined from repeated production failures rather than derived from principle, which is also why they need re-verification over time.

What You Get

  • A catalog of AI-generated visual, copy, and structural tells with concrete replacements
  • Mechanically checkable layout rules (hero fit, eyebrow ratio, bento cell count, CTA discipline)
  • An 8-group pre-flight checklist ordered cheapest-check-first
  • Contrast and consistency-lock verification steps that catch defects static review misses
  • An optional automated pre-scan via the Impeccable detector, merged into the same findings list
  • A reporting format that produces located, actionable findings

When to Use

  • Auditing a generated landing page, portfolio, or marketing site before shipping
  • Diagnosing why a page "looks AI-generated" or "looks templated"
  • Running a final pre-flight pass over frontend output
  • Reviewing a redesign against the page it replaced
  • Establishing ship criteria for machine-generated UI

When NOT to Use

  • Design decisions (tokens, palettes, type scales, grids, motion architecture) -- use design-ux
  • Code correctness, security, blast radius -- use code-review
  • Favicons, OG images, icon sets -- use web-asset-generator
  • Terminal and TUI interfaces -- use design-ux, which owns the monospace side
  • Dashboards, data tables, multi-step forms -- these rules target marketing and portfolio surfaces; product UI has different density constraints. Use impeccable (/impeccable critique or /impeccable audit) when installed
  • Fixing the findings -- this skill returns defects; hand the fix pass to impeccable (/impeccable polish) when installed, else design-ux

Reading Guide

Working onRead
Running the audit end to endpre-flight-check.md
Visual, copy, and decoration tellsai-tells.md
Countable layout defects, hero, nav, CTA, contrastlayout-hard-rules.md

See also

  • design-ux -- for the design decisions this skill audits against
  • code-review -- for correctness, security, and blast radius
  • web-asset-generator -- for producing the favicons and social images this skill expects to exist
  • playwright -- for driving the page to verify rendered contrast and viewport behavior

Common Pitfalls

MistakeWhy It FailsBetter Approach
Reporting a pass/fail verdictGives the author nothing to act onReport each failure with file, line, and fix
Listing rules that passedBuries the findings in noiseReport only failures
Treating tells as universal lawThese are 2026 defaults, not design truthsRe-verify annually; drop entries that stop being defaults
Applying marketing rules to product UIDensity constraints are genuinely differentScope the audit to marketing and portfolio surfaces
Assuming contrast from token namesbg-white plus text-white both look intentionalCheck computed values against the rendered background
Rewriting the pageThe ask is an audit, not a redesignReturn findings; let the author decide the fix
Flagging every em-dash in sourceThe rule is about rendered page textCheck visible strings, not code comments

Key Conventions

  • Countable before subjective: run the mechanical checks first; they need no judgment and catch the most
  • Located findings only: a rule cited without a line number is not a finding
  • Empirical, not eternal: every tell carries a date stamp and an expiry expectation
  • Audit, do not redesign: this skill returns a defect list, not new markup
  • Static is a valid outcome: a page with no motion passes the motion group; half-built motion does not

Attribution

The tell catalog, layout rules, and checklist are adapted from Leonxlnx/taste-skill (MIT, upstream commit ccbc156), restructured for progressive disclosure and scoped to the audit job. Full notice in THIRD-PARTY-NOTICES.md at the repository root.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

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.