探索我们完整的 Claude 技能集合,扩展 AI 代理的能力。
Manages project context and session states across AI conversations using MCP or local storage fallbacks.
Enforces strict documentation standards and quality gates across repository-wide markdown files and AI agent instructions.
Validates code integrity by running syntax checks, linters, type checkers, and unit tests on modified files.
Standardizes infrastructure and CI/CD workflows by enforcing Docker best practices, IaC patterns, and automated quality gates.
Enforces professional Python backend conventions, modern tooling standards, and rigorous quality gates for production-grade development.
Generates and maintains a lean .agentmap.yaml orientation map to help AI agents navigate complex codebases efficiently.
Indexes and displays a structured list of all registered commands, skills, and subagents within the Lore framework.
Analyzes and mitigates time-inconsistent decision-making patterns to prioritize long-term goals over immediate gratification.
Generates four distinct future scenarios by crossing high-impact, high-uncertainty variables to stress-test strategic decisions.
Analyzes codebases thoroughly by searching files and synthesizing evidence-based summaries of specific topics.
Manages your entire Git lifecycle from semantic commits and pull requests to branching strategies and automated release notes.
Implements systematic frameworks and behavioral metrics to analyze user retention and optimize product stickiness through cohort analysis.
Standardizes the creation and maintenance of project README files for monorepo marketplaces using defined structural conventions.
Standardizes the authoring and quality assurance of Claude Code SKILL.md files through rigorous conventions and domain guidance.
Critically evaluates Product Requirements Documents against source prompts to ensure technical feasibility and requirement coverage.
Provides a standardized reference and structural template for creating custom Claude Code plugin skills.
Facilitates collaborative brainstorming sessions by spawning specialized AI agents to provide diverse perspectives on any topic.
Automates the final preparation of pull requests by resolving review findings, running validation gates, and performing safe branch pushes.
Optimizes AI context window usage by managing session state, prioritizing information loading, and coordinating information flow between agents.
Applies bulk triage decisions to SonarCloud security hotspots and vulnerabilities using CSV-based review data and API automation.
Provides expert guidance on Minion development through automated code reviews, documentation search, and best practice enforcement.
Captures and implements actionable improvements immediately after completing tasks to eliminate technical debt and friction.
Coordinates complex coding missions through a structured 7-step multi-agent workflow with built-in risk controls and parallel execution.
Performs structured, multi-scope code reviews using a rigorous 3-pass auditable workflow to identify security vulnerabilities and architectural flaws.
Automates targeted fixes for high-severity code review issues while maintaining project context and coding standards.
Audits code against project-specific standards or extracts implicit conventions from existing codebases to automate documentation and compliance.
Automates the end-to-end deployment and configuration of Minion agent instances on remote Linux servers via SSH.
Optimizes code execution speed and resource efficiency across C++, Rust, and TypeScript using industry-standard engineering patterns.
Corrects architectural violations and signature drift in AI-generated code by aligning it with canonical type definitions.
Simplifies complex source code using relatable analogies, Mermaid flowcharts, and structured step-by-step logic breakdowns.
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