# Anti Slop Review > Use when reviewing a designed or implemented website, web application, or dashboard for generic AI-like copy, unsupported marketing claims, reference collage, arbitrary visual values, repetitive card layouts, fake data, missing states, decorative motion, design-system drift, accessibility, responsive, functional, SEO, or browser-quality failures. Produces evidence-linked findings and blocks relea… - **Type:** Skill - **Install:** `agentstack add skill-bryann2k-skills-anti-slop-review` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [BRYANN2K](https://agentstack.voostack.com/s/bryann2k) - **Installs:** 0 - **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure) - **Latest version:** 0.1.0 - **License:** Apache-2.0 - **Upstream author:** [BRYANN2K](https://github.com/BRYANN2K) - **Source:** https://github.com/BRYANN2K/skills/tree/main/design/anti-slop-review ## Install ```sh agentstack add skill-bryann2k-skills-anti-slop-review ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Anti-Slop Review ## Overview Review whether an interface is specific, truthful, coherent, usable, implemented faithfully, and verified in context. “AI slop” is not a visual genre or list of banned words; it is observable loss of product meaning through unsupported copy, borrowed identity, arbitrary composition, fake data, missing behavior, or decorative polish that outruns function. Do not pass a surface because it looks polished in screenshots. Do not invent evidence, lower severity to meet a deadline, or call skipped checks passed. Claims, authorization, persistence, formulas, accessibility, responsive behavior, performance, SEO delivery, and motion semantics require the evidence appropriate to each claim. ## When to use - Review an interface before design-system approval, implementation completion, merge, release, or publication. - Audit generic copy, landing-page sameness, card-wall composition, trend collage, design drift, fake metrics, missing states, motion excess, accessibility, responsive, or browser behavior. - Compare implemented frontend against approved product, reference, design-system, and project UI artifacts. - Turn subjective “this feels AI-generated” feedback into specific evidence and fixes. Do not use for choosing the initial direction, writing all copy from scratch, penetration testing, or proving backend/security behavior from UI evidence. ## Workflow ### 1. Establish review truth and scope Inspect the requested surface, Git diff, repository instructions, product routes/journeys, `PRODUCT-STORY.md`, `PAGE-COPY.md`, `CLAIMS.md`, `REFERENCE-LEDGER.md`, `DESIGN.md`, `tokens.json`, `COMPONENTS.md`, compiled project UI skill, `MOTION.md` where applicable, implementation, tests, and current browser output. Name baseline failures separately from changes under review. Identify which claims require source, code, test, browser, accessibility-tree, network, data, or human evidence. Load [the review criteria](references/review-criteria.md) for severity and dimension-specific checks. **Complete when:** scope, approved sources of truth, affected journeys/viewports/states, and evidence methods are explicit. ### 2. Audit truth and copy Map visible claims, metrics, testimonials, logos, trust marks, urgency, comparisons, and availability to `CLAIMS.md` and primary evidence. Check that copy: - names the actual user, mechanism, constraint, or task; - does not survive unchanged under a competitor's brand; - uses proof at the supported scope; - preserves human voice rather than formulaic cadence; - gives forms, loading, empty, error, success, permission, and destructive states actionable language; - avoids invented specificity and decorative jargon. Flag a common word only when its usage is vague or unsupported. Do not run a word blacklist as a quality metric. **Complete when:** every visible factual claim is supported or reported, and each copy finding quotes the exact text and explains the product impact. ### 3. Audit direction and composition Compare the surface with the selected visual thesis and no-go list. Check: - attention follows user decisions; - layout area reflects content importance; - sections/components have distinct jobs; - cards, borders, gradients, glows, blur, particles, and illustrations carry meaning; - references were adapted into principles rather than recognizable fragments; - typography, spacing, density, and imagery/data language remain coherent; - product-specific signature is present without overwhelming the task. Uniform grids are not automatically wrong; they fail when unequal information is forced into equal containers without product reason. **Complete when:** each visual finding points to an approved principle or observable task/hierarchy failure rather than personal taste alone. ### 4. Audit design-system fidelity and states Trace rendered values and components to semantic tokens, primitives, and `COMPONENTS.md`. Find: - arbitrary colors, spacing, radius, shadows, typography, durations, or z-index values; - duplicated/forked primitives; - undocumented variants; - broken theme/mode mapping; - missing default, hover, focus-visible, active/selected, disabled, loading, success, error, empty, and skeleton states where applicable; - responsive rules that merely stack without preserving identity, priority, or action context. Inspect source and computed/rendered output. A clean token file does not prove product code uses it. **Complete when:** every divergence is documented, justified and approved, or reported with exact source/rendered evidence. ### 5. Audit product and data behavior Exercise the actual journey with safe representative data. For websites, inspect conversion, form, metadata, canonical/indexability, social, semantic heading, trust/legal, and analytics event behavior. For applications, inspect routes, permissions, state ownership, mutations, retries, and reconciliation. For dashboards, inspect source, grain, formula, freshness, filter scope, card/chart/table agreement, realistic fixtures, permissions, actions, partial failure, and post-action readback. Synthetic data must be labeled and plausible enough to expose layout/state behavior without masquerading as production evidence. **Complete when:** the interface's success, failure, data, and action semantics are tested through the appropriate implementation and source boundaries. ### 6. Audit motion For every material animation, identify its intent: causality, feedback, orientation, continuity, progression, or hierarchy. Verify trigger, timing token, easing, exit, interruption, repeated input, focus, data relationship, and reduced-motion equivalent. Report motion that delays action, implies success early, copies a reference, competes with content, or has no information role. Also report abrupt changes where motion is necessary to preserve spatial understanding. **Complete when:** retained motion earns its cost and normal/reduced behavior is exercised in context. ### 7. Audit browser, accessibility, responsive, and performance evidence Use representative narrow and wide viewports and relevant user settings. Inspect: - landmarks, headings, names, roles, values, descriptions, and announcements; - keyboard order, focus-visible, focus movement/return, skip paths, and traps; - contrast, non-color cues, target size, zoom/reflow, overflow, and content wrapping; - loading, empty, partial, error, permission, offline, and retry states; - console errors, failed/duplicated requests, hydration/runtime warnings; - image/font loading, layout shift, interaction delay, and bundle/network cost proportionately; - metadata and social output in the actual document/response for public pages. Separate unavailable, skipped, failed, and not applicable checks. **Complete when:** browser claims come from fresh post-mutation execution, not source inspection or old screenshots alone. ### 8. Write findings, fix blockers, and rerun Copy [the quality report template](templates/quality-report.md) to `.design-flow/QUALITY-REPORT.md`. Each finding records: - stable ID and severity; - dimension and affected locator; - violated source rule or observable user failure; - evidence; - impact; - smallest durable correction; - verification result after correction. Severities: - `BLOCKER` — false/misleading claim, inaccessible primary task, broken core journey, authorization/data deception, gate bypass, or material unsupported behavior; - `MAJOR` — significant hierarchy, state, responsive, system, motion, conversion, or recovery failure; - `MINOR` — bounded inconsistency with low task impact; - `NOTE` — evidence-backed opportunity, not required for pass. Do not hide findings in a single aggregate score. Fix blockers and relevant majors, rerun affected evidence, then report residual risk honestly. **Complete when:** `## Evidence` and `## Findings` are substantive, every blocker has a disposition, final checks are fresh, and skipped coverage is named. ## Output contract ```text Anti-slop review: PASS | PASS_WITH_NOTES | FAIL | BLOCKED Surface/journey: Approved baseline: Findings - Blocker: - Major: - Minor: - Notes: Dimensions - Truth/copy: PASS | FAIL | SKIPPED - Direction/composition: PASS | FAIL | SKIPPED - Design system/states: PASS | FAIL | SKIPPED - Product/data behavior: PASS | FAIL | SKIPPED - Motion: PASS | FAIL | NOT_APPLICABLE | SKIPPED - Accessibility/responsive: PASS | FAIL | SKIPPED - Marketing/runtime/performance: PASS | FAIL | NOT_APPLICABLE | SKIPPED Evidence - Source/claims: - Static/tests/build: - Browser/viewports/states: - Accessibility tree/keyboard/contrast: - Network/data/action readback: Residual gaps - ``` ## Common pitfalls - Using an unexplained numeric slop score as the verdict. - Treating personal taste as a violation without a principle or task impact. - Banning common words, gradients, cards, or animation categorically. - Reviewing only the happy path or desktop screenshot. - Calling synthetic dashboard data production evidence. - Checking token files without tracing actual rendered values. - Checking hidden buttons instead of server authorization. - Calling metadata SEO readiness without runtime/indexability evidence. - Treating automated accessibility scans as keyboard or screen-reader proof. - Fixing visible symptoms while leaving the system rule or duplicated component unchanged. - Passing skipped browser, role, or reduced-motion coverage silently. ## Verification checklist - [ ] Current diff, source artifacts, implementation, tests, and rendered output were inspected. - [ ] Baseline failures are separated from regressions or scope findings. - [ ] Every visible factual claim maps to evidence and exact allowed scope. - [ ] Copy findings quote exact text and identify product/user impact. - [ ] Composition findings trace to approved direction or observable hierarchy/task failure. - [ ] Rendered values, components, variants, modes, and states trace to the approved design system. - [ ] Product routes, conversion, permissions, state, failure, data, and action behavior were exercised as applicable. - [ ] Dashboard metrics and fixtures are source-defined, reconciled, realistic, and honestly labeled. - [ ] Every material animation has intent, interruption, exit, and reduced-motion evidence. - [ ] Narrow/wide, keyboard/focus/tree/contrast, overflow/wrapping, console/network, and relevant performance checks ran after final mutation. - [ ] Every finding includes severity, locator, evidence, impact, fix, and recheck status. - [ ] Blockers and relevant majors were fixed or explicitly remain blocking. - [ ] Skipped, unavailable, failed, and not-applicable evidence are reported distinctly. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [BRYANN2K](https://github.com/BRYANN2K) - **Source:** [BRYANN2K/skills](https://github.com/BRYANN2K/skills) - **License:** Apache-2.0 Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-bryann2k-skills-anti-slop-review - Seller: https://agentstack.voostack.com/s/bryann2k - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.