Auto Improve
crimeacs/auto-improve
GAN-style iterative improvement loop for any text artifact. An agent skill from crimeacs/auto-improve.
Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design.
$ npx skills add waybarrios/opencode-power-pack --skill ai-slop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install waybarrios/opencode-power-pack ai-slop --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/waybarrios/opencode-power-pack.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-slop .claude/skills/ai-slop && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-slop" agent skill from https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slop into .claude/skills/ai-slop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-slop", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slopType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add waybarrios/opencode-power-pack --skill ai-slop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install waybarrios/opencode-power-pack ai-slop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/waybarrios/opencode-power-pack.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-slop .agents/skills/ai-slop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-slop" agent skill from https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slop into .agents/skills/ai-slop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-slop", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add waybarrios/opencode-power-pack --skill ai-slop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install waybarrios/opencode-power-pack ai-slop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/waybarrios/opencode-power-pack.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-slop .cursor/skills/ai-slop && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-slop" agent skill from https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slop into .cursor/skills/ai-slop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-slop", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/waybarrios/opencode-power-pack.git --path skills/ai-slop--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add waybarrios/opencode-power-pack --skill ai-slop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install waybarrios/opencode-power-pack ai-slop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/waybarrios/opencode-power-pack.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-slop .gemini/skills/ai-slop && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-slop" agent skill from https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slop into .gemini/skills/ai-slop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-slop", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install waybarrios/opencode-power-pack ai-slopInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add waybarrios/opencode-power-pack --skill ai-slop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/waybarrios/opencode-power-pack.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-slop .github/skills/ai-slop && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-slop" agent skill from https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slop into .github/skills/ai-slop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-slop", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add waybarrios/opencode-power-pack --skill ai-slop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install waybarrios/opencode-power-pack ai-slop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/waybarrios/opencode-power-pack.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-slop .opencode/skills/ai-slop && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-slop" agent skill from https://github.com/waybarrios/opencode-power-pack/tree/main/skills/ai-slop into .opencode/skills/ai-slop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-slop", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ai-slopOperational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design.
AI Slop is an agent skill from waybarrios/opencode-power-pack. Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside frontend-design.
Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Education, covering Quizzes and assessments, Landing pages and E-commerce operations. The repository describes itself as: 54 rigorous skills for Codex, OpenCode, and Pi: code review, security audit, feature development, frontend design, MCP tools, Hugging Face ML/training, and more. The licence is MIT.
12 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 9dccb6d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AI Slop loads about 3.6k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 1,783 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from waybarrios/opencode-power-pack at commit 9dccb6d, republished under its MIT licence (© waybarrios). 1,783 words, ~3,635 tokens.
.claude/skills/ai-slop/SKILL.md (or your agent's skills folder).Scope: marketing sites, product interfaces, dashboards, portfolios, editorial pages, and e-commerce. Complements frontend-design: that skill builds the interface, this one is the detailed rubric for judging whether the result is generic ("AI slop") or genuinely fit for the product.
This is not a universal style guide. It does not ban a visual style merely because AI systems use it often — a gradient, card grid, serif headline, glass surface, or dark theme may be appropriate. It becomes a slop signal when used by reflex rather than because the product, audience, content, interaction, or brand requires it.
MUST/MUST NOT are required for acceptance; SHOULD/SHOULD NOT are default rules whose deviations need a written rationale; MAY is optional and context-dependent.
AI slop is superficially competent output that lacks sufficient intention, grounding, specificity, coherence, truthfulness, or product fit. It usually shows up as one or more of:
Output is not slop merely because AI helped produce it — a result can be AI-assisted and still strong when it's grounded in real product/user context, deliberately art-directed, specific, factually honest, coherent, accessible, edited, browser-validated, and hard to transplant unchanged to another product. Human-made work can also be slop; the classification concerns the output, not proof of authorship.
PRODUCT.md (or equivalent) with explicit users, jobs, constraints, and a traceable reason per section. Repair: cut unsupported sections, rewrite around concrete user tasks.[NEEDS INPUT], "Price on request," or clearly labeled sample data instead; keep an evidence ledger for verifiable claims; mark fictional demo data as demo data.DESIGN.md with semantic tokens (color, type, spacing, radius, elevation, motion) that components actually consume, and a documented exception when something breaks the system.Classify the result as slop when: one blocking issue exists, three or more dimensions score 3, the same reflex repeats across multiple registers (color + typography + layout + copy), or both quick tests fail.
PRODUCT.md: product/offer, target users, primary jobs, key tasks, real facts vs. assumptions, non-goals, content gaps, accessibility target, success criteria.DESIGN.md: art-direction sentence, brand attributes, anti-references, extracted principles from visual references, palette and semantic color roles, typography roles, spacing/grid system, radius/border/elevation/material rules, imagery direction, motion rules, component vocabulary, responsive principles, intentional exceptions.EVIDENCE.md: for every externally verifiable claim — exact claim, source, confidence, allowed wording, where it appears. Unsupported claims MUST NOT ship.A single self-review is insufficient. Gate through, in order:
Track two separate results — never collapse them into one number:
When slop is detected: name the failed dimension, cite visible/source-level evidence, identify whether the cause is missing context, a model reflex, incomplete implementation, or weak review, remove unsupported content before adding polish, fix the system or rule (not just the symptom), re-run the deterministic/browser/screenshot checks, compare pairwise against the previous version, and record what changed and why.
Do not turn "anti-slop" into another recognizable house style. Don't automatically replace dark-neon with cream-editorial, sans-serif with giant italic serif, cards with arbitrary asymmetry, gradients with flat beige, polished copy with forced quirkiness, or standard layouts with scroll gimmicks. The goal isn't to look less like one AI default by adopting another — it's decisions justified by the project.
Separate rules into two layers so the rubric doesn't fight yesterday's cliché while ignoring tomorrow's:
dark-purple-cyan-glass-default (current LLM tech-product default — flag when used without brand rationale) or overused-default-fonts: Inter, Roboto, Geist, Plus Jakarta Sans, Space Grotesk (exception: Roboto Mono for monospace, Roboto Condensed for display). Review temporal rules at their review date; drop them if the trend faded, otherwise renew. A temporal rule MUST NOT become a new predictable default — after banning a trend, check whether the agent just adopted the next fashionable alternative instead.No blocking issue remains; primary tasks work in the browser; claims are supported or explicitly labeled; the accessibility target is met; screenshots pass responsive review; the design is internally coherent; prominent decisions have written rationale; the substitution test doesn't reveal broad interchangeability; pairwise review prefers the final result over its control/previous version; remaining known limitations are documented.
AI slop is superficially polished but insufficiently intentional, grounded, specific, coherent, truthful, or product-fit output. Don't judge styles in isolation — detect default reflexes, interchangeability, unsupported content, system inconsistency, decorative excess, incomplete interaction, and unreviewed defects. Ground every major decision in PRODUCT.md/DESIGN.md, verify claims through EVIDENCE.md, test real browser tasks and responsive screenshots, and use pairwise review instead of a self-assigned score. A common visual treatment is fine when deliberate, coherent, accessible, and justified by the project.
© waybarrios, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/ai-slop of waybarrios/opencode-power-pack.
Open the folder on GitHubat commit 9dccb6d
AI Slop next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Slop this skillwaybarrios/opencode-power-pack | 534 | — | ~3.6k | Automated safety check: Pass | MIT | |
| Auto Improvecrimeacs/auto-improve | 135 | — | ~651 | Automated safety check: Pass | MIT | |
| Trust Signalsthedaviddias/Front-End-Checklist | 74k | — | ~619 | Automated safety check: Pass | MIT | |
| CloudbaseLeoYeAI/openclaw-master-skills | 2.2k | 1 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Scenario Product Shotsscenario-labs/skills | 946 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Ecommerce Landing Pagenexscope-ai/eCommerce-Skills | 1.1k | — | ~617 | Automated safety check: Pass | MIT |
crimeacs/auto-improve
GAN-style iterative improvement loop for any text artifact. An agent skill from crimeacs/auto-improve.
thedaviddias/Front-End-Checklist
A skill your agent uses when applies especially to e-commerce checkouts, contact/lead forms, pricing pages, and YMYL (Your Money or Your Life) content.
LeoYeAI/openclaw-master-skills
CloudBase is a full-stack development and deployment toolkit for building and launching websites, Web apps, 微信小程序 (WeChat Mini Programs), and mobile apps with backend, database, hosting, cloud…
scenario-labs/skills
A skill your agent uses when producing product photography with Scenario from a real product photo: e-commerce packshots on white, transparent, or brand backgrounds, lifestyle scenes placing the…
nexscope-ai/eCommerce-Skills
Audit and optimize e-commerce landing pages for conversion. An agent skill from nexscope-ai/eCommerce-Skills.
saoudi-h/solar-icons
UI/UX design intelligence for web and mobile. An agent skill from saoudi-h/solar-icons.
waybarrios/opencode-power-pack
Verify or select a SageMaker execution role before creating models, endpoints, or training jobs.
waybarrios/opencode-power-pack
Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion.
waybarrios/opencode-power-pack
Train object-detection, image-classification, or SAM segmentation models on Hugging Face Jobs.
waybarrios/opencode-power-pack
Run CodeQL database creation and security queries, add data-extension models, or process CodeQL SARIF.
waybarrios/opencode-power-pack
Run Semgrep static analysis across a codebase, optionally using Semgrep Pro for cross-file taint analysis.
waybarrios/opencode-power-pack
Detects fail-open insecure defaults (hardcoded secrets, weak auth, permissive security) that allow apps to run insecurely in production.
Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. AI Slop is an agent skill from waybarrios/opencode-power-pack. Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design.
AI Slop fits situations like: tasks that involve Quizzes and assessments; tasks that involve Landing pages; tasks that involve E-commerce operations.
Run `npx skills add waybarrios/opencode-power-pack --skill ai-slop -a claude-code`. Or copy the skill folder (skills/ai-slop in waybarrios/opencode-power-pack) into .claude/skills/ai-slop in your project. Claude Code loads it when a task matches its description.
Run `npx skills add waybarrios/opencode-power-pack --skill ai-slop -a codex`. Or copy the skill folder (skills/ai-slop in waybarrios/opencode-power-pack) into .agents/skills/ai-slop in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add waybarrios/opencode-power-pack --skill ai-slop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-slop, .gemini/skills/ai-slop, .github/skills/ai-slop and .opencode/skills/ai-slop in your project.
SKILL.md names no scripts, command-line tools or credentials: AI Slop is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
AI Slop is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.6k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AI Slop: Auto Improve (crimeacs/auto-improve, 135 stars), Trust Signals (thedaviddias/Front-End-Checklist, 74k stars), Cloudbase (LeoYeAI/openclaw-master-skills, 2.2k stars) and Scenario Product Shots (scenario-labs/skills, 946 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
waybarrios (a GitHub user) maintains it in waybarrios/opencode-power-pack, which has 534 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on October 6, 2026.
Source: waybarrios/opencode-power-pack on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.