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SkillsMP a collecté 16 skills depuis seanGSISG/crispy-claude. Ouvrez un skill pour examiner sa source et ses détails.
Affichage de 16 skills collectés sur 16.
Use after plan is written to validate implementation plans across completeness, quality, feasibility, and scope dimensions - spawns specialized validators for failed dimensions and refines plan interactively before execution
Langue du texte source : anglais
Use when creating pull requests to auto-generate PR descriptions from plan, execution context, and memory - handles pre-flight checks, description generation, and GitHub CLI integration
Langue du texte source : anglais
Use when saving workflow state to Serena MCP memory at research, planning, execution, or completion stages - enables resuming work later with /cc:resume command
Langue du texte source : anglais
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
Langue du texte source : anglais
Use when researching GitHub issues, PRs, and discussions for community solutions and known gotchas - searches via WebSearch with site filters and extracts problem-solution patterns
Langue du texte source : anglais
Use when researching best practices, tutorials, and expert opinions using WebSearch and WebFetch tools - assesses source authority and recency to synthesize findings with citations
Langue du texte source : anglais
Use when researching library documentation with Context7 MCP tools for official patterns and best practices
Langue du texte source : anglais
Use when partner provides a complete implementation plan to execute in controlled batches with review checkpoints - loads plan, reviews critically, executes tasks in batches, reports for review between batches
Langue du texte source : anglais
Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes
Langue du texte source : anglais
Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file paths, complete code examples, and verification steps assuming engineer has minimal…
Langue du texte source : anglais
Use after writing-plans to decompose monolithic plan into individual task files and identify tasks that can run in parallel (up to 2 subagents simultaneously)
Langue du texte source : anglais
Use when brainstorming completes and user selects research-first option - manages parallel research subagents (up to 4) across codebase, library docs, web, and GitHub sources, synthesizing findings and auto-saving to memory before planning
Langue du texte source : anglais
Use when exploring codebases with Serena MCP tools for architectural understanding and pattern discovery - guides efficient symbolic exploration workflow minimizing token usage through targeted symbol reads, overview tools, and progressive narrowing
Langue du texte source : anglais
Use when setting up project-specific agents via /cc:setup-project or when user requests custom agents for their codebase - analyzes project to create specialized, project-aware implementer agents that understand architecture, patterns, dependencies, and…
Langue du texte source : anglais
Use when setting up project-specific skills via /cc:setup-project or when user requests custom skills for their codebase - analyzes project to create specialized skills that capture architecture knowledge, coding conventions, testing patterns, and deployment…
Langue du texte source : anglais
Use when executing decomposed plans with parallel batches - dispatches up to 2 fresh subagents per batch with code review between batches, enabling fast parallel iteration with quality gates
Langue du texte source : anglais