Slop Cop
/install slop-cop
slop-cop
A visual-design referee. Given one or more image assets plus a decision context, produce strict per-asset verdicts (SHIP, FIX, or KILL) and, when multiple candidates compete for one slot, a ranked recommendation with placement reasoning.
The goal: stop hallucinated text, melted hands, off-brand vibes, and obvious AI artifacts from reaching production.
When to invoke
- User has 1–N images and a decision to make ("which works best for hero?", "is this safe to ship?", "does this fit my brand?").
- User wants a second opinion on a visual choice before deploy.
- User asks to audit a landing page or compare AI-generated variants.
- User explicitly says "slop check" / "is this AI slop?"
Inputs the skill needs
Before analysis, confirm or infer:
- Image paths — 1 or more local file paths or URLs.
- Decision context — what slot/role is this for? Examples:
"hero banner at 1200x600","square avatar 1024x1024","mobile card at 4:5","is this safe to ship anywhere?". - Target render size / aspect ratio — if relevant (e.g. hero rendered at 600x600 with rounded corners and a 4px border).
- Brand palette / style — hex colors and a one-line style descriptor when available (e.g.
"navy #0f3a66 / orange #f3812a, cartoon illustration"). - Mode — single-asset audit (
SHIP/FIX/KILL) or comparative pick (rank + recommend one).
If the user does not provide brand context, ask once. If they decline, proceed without brand-fit scoring and note it in the verdict.
Workflow
1. Run the vision pass
For each image, call the OpenClaw image tool with the strict checklist prompt in references/vision-prompt-template.md. Pass one image per call when possible — keeps the model focused. Use images (multi) only for explicit side-by-side comparison once each has been individually vetted.
The prompt template forces the vision model to enumerate findings against a fixed checklist instead of writing vibes-based prose.
2. Score against the full checklist
The mandatory checklist lives in references/checklist.md. Every asset must be scored on:
- Hallucination scan — gibberish text, extra/melted fingers, broken anatomy, duplicated objects, watermarks, AI signatures, lighting that contradicts itself.
- Legibility at target size — can any text on the asset be read at its actual render size?
- Responsive safety — will the focal subject survive cropping to 16:9, 4:5, 1:1, and 9:16? Identify the focal point in pixel/percent terms.
- Cross-browser / format — transparency needs (PNG/WEBP vs JPG), color profile concerns (sRGB vs P3), iOS Safari quirks.
- Brand fit — if palette/style provided, check coherence; flag major mismatches.
- Format / size sanity — actual dimensions, file size for web, aspect-ratio fit for the target slot.
3. Assign a verdict per asset
Use exactly one verdict word per asset, plus a one-sentence reason. No hedging, no "looks okay but...".
| Verdict | Meaning |
|---|---|
SHIP |
Clean. Deploy as-is. |
FIX |
Salvageable with a specific edit (crop, recolor, regenerate text region, swap to different aspect). State the fix. |
KILL |
Do not use. Hallucination, off-brand, broken anatomy, or wrong-tool-for-the-job. |
Hard kill triggers (any one of these = automatic KILL):
- Visible hallucinated/gibberish text on a graphic shipping to prod.
- Extra/missing/melted fingers on a human or human-adjacent character.
- Visible watermark or AI-tool signature.
- Major brand-palette violation (when palette provided) that can't be fixed by recolor.
See references/anti-patterns.md for the full kill list and CSS-level gotchas that come up on real sites.
4. Comparative mode (multiple candidates, one slot)
When the user is choosing between assets for a single slot:
- Verdict each candidate individually first.
- Drop all
KILLverdicts from the running. - Rank remaining
SHIPandFIXcandidates by fit-to-context (brand match > focal-point survival > legibility > polish). - Recommend one. Name the file path, the slot, and one-sentence placement reasoning.
- If every candidate is
KILLorFIX, recommend regeneration with a brief brief.
5. Output format
Return a structured response:
## Verdicts
- \x3Cfilename> — VERDICT — one-sentence reason
- \x3Cfilename> — VERDICT — one-sentence reason
...
## Anti-patterns flagged
- (optional) bullet list of CSS/HTML/format gotchas detected from context
## Recommendation
\x3CFor comparative mode: which file goes in which slot, why, and any FIX steps needed before deploy.>
## Deploy notes
\x3CConcrete file paths, target dimensions, format conversions, and any CSS/HTML lines that should change. Do NOT execute deploys — describe them.>
Keep it tight. No filler, no "great question."
Failure modes
- Vision tool unavailable / errors out — Document the failure, then make a best-effort judgment from filename, file metadata (
identify/file/exiftoolif available), and decision context. Mark the verdict asBEST-EFFORTin parens and flag that a manual eyeball is required before ship. - No brand context provided — Proceed; note "no brand check performed."
- Asset is a wordmark/logo — Skip hallucination scan for stylized typography (intentional design ≠ gibberish), but still check legibility, format, and brand-palette match.
References
- references/vision-prompt-template.md — exact prompt to send to the vision tool.
- references/checklist.md — the full per-asset checklist.
- references/anti-patterns.md — concrete bugs and CSS/HTML pitfalls to flag.
- references/promo-copy.md — optional marketing copy for this skill (not loaded during normal use).
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install slop-cop - After installation, invoke the skill by name or use
/slop-cop - Provide required inputs per the skill's parameter spec and get structured output
What is Slop Cop?
Judges visual design assets and AI-generated images before they ship. Use when the user wants to compare design options, choose between asset variants for a... It is an AI Agent Skill for Claude Code / OpenClaw, with 45 downloads so far.
How do I install Slop Cop?
Run "/install slop-cop" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Slop Cop free?
Yes, Slop Cop is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Slop Cop support?
Slop Cop is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Slop Cop?
It is built and maintained by Chad Keith (@chchchadzilla); the current version is v0.1.0.