发现productivity & workflow类别的 Claude 技能。浏览 170 个技能,找到适合您 AI 工作流程的完美功能。
Accelerates debugging and task completion by orchestrating multiple independent agents to work concurrently on separate problem domains.
Enhances AI response quality by 45-115% through research-backed techniques like expert personas and stakes-based framing.
Automates repetitive development tasks through a continuous iteration loop with clear, verifiable completion criteria.
Automates the organization of messy invoices and receipts by extracting key data, renaming files consistently, and sorting them into logical tax-ready folders.
Standardizes the software development lifecycle within Claude Code through systematic analysis, multi-agent exploration, and structured code reviews.
Enhances AI response quality by up to 115% using research-backed techniques like persona assignment and stakes-based framing.
Updates and appends data to Google Sheets spreadsheets directly via terminal commands.
Transforms vague user inputs into highly structured, high-performance specifications using the TCRO framework and phase-specific clarification.
Executes multiple Claude Code agents simultaneously using wave-based orchestration and automated environment isolation.
Orchestrates multi-phase research across codebases and documentation to provide evidence-backed insights and architectural synthesis.
Implements technical specifications through autonomous, phase-based code execution with deep planning and semantic commits.
Automates repetitive development tasks through a continuous iteration loop with objective completion criteria and safety caps.
Transforms ambiguous user input into high-precision, structured TCRO prompts to maximize AI output quality and consistency.
Implements a continuous iteration loop pattern for autonomous development and automated verification tasks.
Automates repetitive development tasks through a continuous iteration loop with objective completion criteria and safety guards.
Transforms vague user inputs into highly structured, actionable TCRO prompts to maximize AI response quality and accuracy.
Transforms vague user inputs into structured, high-quality prompts using the TCRO framework to maximize AI performance and consistency.
Generates comprehensive, test-driven implementation plans that break down complex requirements into bite-sized, executable tasks.
Conducts deep, multi-phase investigations across codebases and documentation using specialized AI agents for evidence-based decision making.
Transforms vague user inputs into structured, high-performance prompts using the TCRO framework and phase-specific clarification.
Transforms vague user inputs into structured TCRO specifications to maximize AI output quality and consistency.
Enhances AI response quality by 45-115% using research-backed prompting techniques like expert personas and step-by-step reasoning.
Automates repetitive development tasks using a systematic while-loop pattern with objective completion criteria.
Orchestrates multi-phase investigations across codebases, documentation, and external sources to generate evidence-based insights.
Transforms vague user input into highly structured, TCRO-formatted prompts to maximize AI output quality and consistency.
Removes AI-generated verbosity, conversational fillers, and redundant comments to improve information density and clarity.
Bootstraps repository-specific GitHub Copilot instructions and configurations to optimize coding agent performance with minimal noise.
Optimizes Claude Code's context window usage through token budgeting, efficient CLAUDE.md structuring, and advanced conversation management.
Generates structured, objective technical Request for Comments (RFC) documents and architectural proposals with rigorous trade-off analysis.
Maintains a clean workspace by organizing project artifacts and safely removing temporary development files.
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