visual-product-slop-audit

name	visual-product-slop-audit
description	Use when auditing imagery, brand assets, UI screens, or AI product features for visual and product slop. Unlike ai-slop-typography-audit, this excludes type; written-copy slop routes to the digital-research engine.
metadata	{"portable":true,"category":"00-cross-cutting-ops-qa-a11y","compatible_with":["claude-code","codex"]}

Visual & Product Slop Audit

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com.

Use When

• Reviewing AI-generated or AI-assisted imagery, key art, thumbnails, or brand/marketing assets.
• Auditing a UI screen or a product feature that embeds generative AI.
• Gate-checking any visual deliverable before it ships under the Chwezi name.
• Checking a specific artifact against the current slop doctrine after the doctrine has already been refreshed.

Do Not Use When

• The concern is the typeface/type system — use ai-slop-typography-audit.

• The concern is written copy (preambles, buzzword salad, vague attribution) — that is a writing concern owned by the digital-research-engine (anti-ai-slop); route there.

• The question is whether the definition of AI slop, a banned font, or a current visual tell has changed - use slop-doctrine-refresh-and-research-loop first, then return here for artifact audit.

Required Inputs

Input	Supplied by	Required?	Why
Assets, screens, or live feature	Requester	yes	Defines the audit surface
Audience, channel, and stakes	Product or brand brief	yes	Calibrates severity
Current slop taxonomy	Design doctrine	yes	Prevents stale or invented tells

• The asset(s) or screens (images, mockups, the live UI, or a description of the feature).
• The context and audience, and whether it is public-facing (raises the bar — corporate slop is the highest-backlash failure, per doctrine/references/ai-slop-taxonomy.md).

Workflow

1. Run the visual tells checklist (references/visual-tells-checklist.md, which operationalises ai-slop-taxonomy.md → Visual & video tells): waxy skin, melted backgrounds, gibberish text, floating objects, extra fingers/impossible anatomy, warped/misspelled logos, uncanny faces, mismatched lighting. Current 2026 AI-image tells (the classic six-finger artifact is largely fixed in late-2025/2026 models, so the tells migrated): plastic "default-render" lighting & creamy bokeh, texture-too-perfect / uniform-frequency detail, micro-anatomy & accessory errors visible only on zoom (teeth, earrings, watch faces, fused hair), garbled small text / UI chrome / gauges, impossible reflections & re-tiling patterns, and the "no-author" style-blend aesthetic — perfect, even, styleless competence that looks made by nobody. The 2026 rule of thumb: the tell is now the absence of authored specificity, not a hard anomaly.
2. Run the product/interface tells checklist: AI feature where nav/search was faster; ungrounded chatbot that can invent commitments; generative output with no verifiability/undo; decorative "AI" badges/gradients with no user benefit.
3. Classify each finding — critical (public-facing visual anomaly, warped logo, halluc
   inating bot) vs major/minor.
4. Decide remake vs remediate. Anomalous AI imagery is remade or replaced (art-directed, or real photography/illustration), not patched. Product slop is removed or grounded.
5. State the human-craft alternative — what a skilled designer would ship instead (per the Mission: distinct, authored, not templated).
6. Report findings → fixes with before/after.

Anti-Patterns

• "Touching up" a six-fingered hero image instead of remaking it.
• Keeping an AI feature because it's impressive when a search bar served users better.
• Treating an AI gradient/badge as design.
• Declaring any polished generated image slop without naming a concrete tell and evidence.
• Spot-fixing anatomy, text, or logo corruption instead of remaking the source asset.

Quality Standards

• Inspect focal details at delivery resolution and evaluate the feature in its actual flow.
• Separate anomalies, convergence, provenance gaps, and product-risk findings.
• Block public release for corrupted identity, anatomy, text, or ungrounded consequential output.

Outputs

Output	Consumer	Evidence / acceptance
Severity-rated finding register	Designer and owner	Asset location, tell, evidence, and taxonomy mapping
Remake/remediate disposition	Production team	Named human-craft alternative for every finding
Gate verdict	Pre-launch QA	PASS, CONDITIONAL, or BLOCKED with unresolved risks

• A findings list (tagged critical/major/minor with the tell it breaks) and a stated, human-craft remediation ready to apply.

Examples

• See examples/slop-audit-filled.md for a complete severity and disposition register.

Decision Rules

Condition	Decision	Wrong-choice failure
Identity, anatomy, or embedded text is corrupted	Remake or replace and block ship	Visible anomaly damages trust
Asset is competent but unauthored and generic	Re-art-direct with a specific point of view	Convergent brand work ships
AI feature lacks grounding, verification, or undo	Remove or ground it	Generated output is treated as fact
Evidence is ambiguous	Mark conditional and seek source/provenance	Suspicion is presented as proof

Capability Contract

Read and high-resolution visual inspection are required. Review is read-only unless remediation is authorised. Network access is optional for provenance checks; editing or generation must preserve brand and usage rights.

Degraded Mode

Without original-resolution assets or live-flow access, audit the supplied evidence, mark hidden details unverified, and withhold a pass. Recover by requesting crops, source files, or a recorded walkthrough.

• examples/slop-audit-filled.md — a real before/after audit of a Maduuka landing-page hero + embedded AI chat panel: findings (tagged critical/major/minor) → remake/remediate dispositions with the human-craft alternative named for each.

References

• references/visual-tells-checklist.md — the concrete, tickable image + product/interface tells (incl. the current 2026 AI-image tells), citing the taxonomy.
• doctrine/references/ai-slop-taxonomy.md, doctrine/design-doctrine.md (Mission).
• doctrine/references/living-slop-refresh-protocol.md and slop-doctrine-refresh-and-research-loop for refreshing changing slop definitions.
• Sibling audits: ai-slop-typography-audit (type); digital-research anti-ai-slop (writing).