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Found 1,747 Skills
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.
Multi-Model Collaboration — Invoke gemini-agent and codex-agent for auxiliary analysis **Trigger Scenarios** (Proactive Use): - In-depth code analysis: algorithm understanding, performance bottleneck identification, architecture sorting - Large-scale exploration: 5+ files, module dependency tracking, call chain tracing - Complex reasoning: solution evaluation, logic verification, concurrent security analysis - Multi-perspective decision-making: requiring analysis from different angles before comprehensive judgment **Non-Trigger Scenarios**: - Simple modifications (clear changes in 1-2 files) - File searching (use Explore or Glob/Grep) - Read/write operations on known paths **Core Principle**: You are the decision-maker and executor, while external models are consultants.
SCPR (Situation-Complication-Problem-Recommendation) framework for structured problem solving and executive communication. Use when users need to structure strategic arguments, analyze business situations, create executive summaries, or develop clear problem statements using McKinsey-style communication. Apply when structuring recommendations, writing memos, or organizing strategic thinking.
This skill generates comprehensive metrics reports for intelligent textbooks built with MkDocs Material, analyzing chapters, concepts, glossary terms, FAQs, quiz questions, diagrams, equations, MicroSims, word counts, and links. Use this skill when working with an intelligent textbook project that needs quantitative analysis of its content, typically after significant content development or for project status reporting. The skill creates two markdown files - book-metrics.md with overall statistics and chapter-metrics.md with per-chapter breakdowns - in the docs/learning-graph/ directory.
Evaluate, optimize, and enhance prompts using 58 proven prompting techniques. Use when user asks to improve, optimize, or analyze a prompt; when a prompt needs better clarity, specificity, or structure; or when generating prompt variations for different use cases. Covers quality assessment, targeted improvements, and automatic optimization across techniques like CoT, few-shot learning, role-play, and 50+ more.
Unified code review system — dispatches the right review agents for the situation. Use when reviewing code for quality, bugs, compliance, or before merging.
Generate or update tests for changed files in the current git branch, using statement coverage as the evaluation metric (target: 80%+). Use when: (1) the user asks to "write tests for my changes", "add tests for the current branch", or "improve coverage", (2) after implementing a feature to ensure adequate test coverage, (3) before a PR to verify changed code is tested. Supports Vitest and Cargo projects. Invoked with /test-generator or phrases like "generate tests", "test my changes", "cover the diff".
Guide to effective Claude Code skill authoring using TDD methodology and persuasion principles. Use when creating new skills, improving compliance, or validating quality before deployment. Do not use for evaluating existing skills (use skills-eval) or analyzing architecture (use modular-skills). Follow the Iron Law: write a failing test before writing any skill.
Run SEO and GEO audits on URLs covering technical SEO, content quality, E-E-A-T signals, and AI citation readiness. Use when evaluating search performance or diagnosing ranking issues.
Product vision, roadmap development, and go-to-market execution with structured prioritization frameworks. Use when evaluating features, planning product direction, or assessing market fit.
This skill should be used when performing AI-powered mutation testing to evaluate and improve unit test quality. It generates targeted code mutants, runs tests to identify surviving mutants, and strengthens or creates tests to kill them. Accepts a file path, directory, or defaults to git diff changed files.
Progressive context refinement pattern for subagents. Solves the problem of agents not knowing what context they need until they start working. Uses a 4-phase loop: DISPATCH, EVALUATE, REFINE, LOOP.