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Found 219 Skills
Use when one agent is implementing code and another agent must review the resulting changes, compare the summary against the actual files, decide whether to fix now or move on, and write the next tightly scoped prompt with context handoff guidance.
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
Guide for creating agent skills that follow the Agent Skills specification. Use when user wants to create, write, draft, or improve a skill. Covers structure, description optimization, progressive disclosure, scripts, and evaluation.
A methodology for iteratively improving agent-facing text instructions (skills / slash commands / task prompts / CLAUDE.md sections / code-generation prompts) by having a bias-free executor actually run them and evaluating two-sidedly (executor self-report + instruction-side metrics). Keep iterating until improvements plateau. Use it right after creating or substantially revising a prompt or skill, or when you want to attribute an agent's unexpected behavior to ambiguity on the instruction side.
GPT Image 2 prompt gallery, agentic skill, and CLI for OpenAI image generation and editing with curated prompts and reference workflows
An image generation/editing Skill for GPT Image 2. It can be used in 3 environments: (A) Garden Local Mode: directly generate and save images via OpenAI-compatible APIs; (B) Host-Native Mode: treat this Skill as a prompt engineering guide, and pass the rendered prompt to the image tool built into the host Agent for image generation; (C) Advisor Mode: degrade to a high-quality prompt consultant when the host has no image tools. It covers 18 major categories and over 80 structured templates, including scenarios such as posters, UI, products, infographics, academic figures, technical architecture diagrams, comics, avatars, process boards, storyboards, IP peripherals, and editing workflows.
Generate AI images using Gemini image generation API. Use this skill when content needs images - thumbnails, social posts, blog headers, or creative visuals. Follows an iterative workflow - brainstorm concepts, select direction, generate in multiple styles, then produce via API.
Build tools that agents can use effectively, including architectural reduction patterns
Chain-of-Verification (CoVe) prompting system. Converts lazy prompts into rigorous 4-stage verified output. Use for any code generation, debugging, or implementation task. Automatically invoked by wavybaby for medium/high complexity tasks. Reduces hallucinations and catches subtle bugs.
Activate when user provides a prompt, SKILL.md, or agent instruction and requests optimization. Transforms weak instructions into reliable, enforceable agent protocols.
Generate PhD-level expert agent prompts for Claude Code. Creates comprehensive 500-1000 line agents with detailed patterns, code examples, and best practices. Triggers on: spawn agent, create agent, generate expert, new agent, agent genesis.
Build, validate, and deploy LLM-as-Judge evaluators for automated quality assessment of LLM pipeline outputs. Use this skill whenever the user wants to: create an automated evaluator for subjective or nuanced failure modes, write a judge prompt for Pass/Fail assessment, split labeled data for judge development, measure judge alignment (TPR/TNR), estimate true success rates with bias correction, or set up CI evaluation pipelines. Also trigger when the user mentions "judge prompt", "automated eval", "LLM evaluator", "grading prompt", "alignment metrics", "true positive rate", or wants to move from manual trace review to automated evaluation. This skill covers the full lifecycle: prompt design → data splitting → iterative refinement → success rate estimation.