jhonatan-oliveiradevjhonatan-oliveiradev/agent-skills/skills/auditing-pixel-perfect-frontend/SKILL.mdauditing-pixel-perfect-frontend
Skill1 starsChanged 3 months agoMITView on GitHub
Use when reviewing an implemented frontend against Figma, screenshots, a live reference, or explicit visual acceptance criteria and concrete visual regressions must be identified and prioritized.
In this repository65 other files it gives its agents.
- analyzing-change-blast-radiusSkill
- analyzing-developer-career-opportunitiesSkill
- art-directing-web-interfacesSkill
- assessing-developer-proficiencySkill
- auditing-dependency-riskSkill
- bootstrapping-modern-web-appsSkill
- brag-slimSkill
- building-brand-guidelinesSkill
- building-conversion-product-pagesSkill
- building-developer-career-roadmapsSkill
- building-hybrid-game-assetsSkill
- building-premium-nextjs-interfacesSkill
- building-project-showcasesSkill
- building-regression-testsSkill
- building-reliable-node-api-boundariesSkill
- choosing-application-architectureSkill
- craft-premium-motionSkill
- creating-character-sprite-pipelinesSkill
- defining-brand-strategySkill
- designing-action-combatSkill
- designing-developer-portfolio-evidenceSkill
- designing-relational-data-modelsSkill
- designing-software-boundariesSkill
- designing-test-strategiesSkill
- designing-ui-systemsSkill
- designing-visual-identitiesSkill
- documenting-architecture-decisionsSkill
- editing-for-clarity-and-toneSkill
- engineering-gsap-animationsSkill
- evaluating-developer-proficiencySkill
- evolving-postgres-schemas-safelySkill
- humanizing-generated-proseSkill
- implementing-reference-faithful-uiSkill
- investigating-codebase-semanticallySkill
- managing-implementation-slicesSkill
- mapping-existing-codebase-structureSkill
- naming-brands-and-productsSkill
- optimizing-frontend-motion-performanceSkill
- orchestrating-cinematic-web-motionSkill
- planning-codebase-changes-with-evidenceSkill
- planning-engineering-workSkill
- planning-launch-distributionSkill
- planning-safe-refactorsSkill
- planning-written-communicationSkill
- preparing-project-launchSkill
- profiling-postgres-query-performanceSkill
- reconstructing-images-as-threejsSkill
- reviewing-api-securitySkill
- reviewing-apple-platform-interfacesSkill
- reviewing-pull-requestsSkill
- reviewing-web-securitySkill
- selecting-working-methodsSkill
- shipping-github-vercel-changesSkill
- teaching-developer-conceptsSkill
- testing-integration-boundariesSkill
- testing-playable-gamesSkill
- testing-web-applications-end-to-endSkill
- threat-modeling-applicationsSkill
- tracing-code-execution-pathsSkill
- translating-figma-to-nextjsSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
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
- Distinctive: line 26
Do not accept “close enough” when the user explicitly asked for fidelity.
≈ “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
Auditing Pixel-Perfect Frontend
Audit method
- Capture the implementation at the same viewport dimensions as the reference.
- Compare macro layout before details: section height, container width, column proportions, alignment, whitespace.
- Compare typography: family, size, weight, line-height, letter-spacing, wrapping, clipping.
- Compare media: crop, object position, aspect ratio, scale, masks, corner radius.
- Compare components and states: borders, icon size, control density, hover/focus, arrows, labels, disabled/loading.
- Repeat on mobile independently.
Severity
- P0: broken interaction, unreadable/hidden content, severe responsive failure.
- P1: major composition mismatch visible immediately.
- P2: noticeable typography, crop, alignment, or state mismatch.
- P3: polish-level spacing, radius, shadow, or micro-detail.
Output
Lead with findings, not praise. For each issue, state location, expected behavior, observed behavior, severity, and the most likely implementation owner.
Rule
Do not accept “close enough” when the user explicitly asked for fidelity. Conversely, do not chase subpixel differences before resolving structural mismatches.
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.