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Found 37 Skills
Use when designing system architecture, making high-level technical decisions, or planning major system changes. Focuses on structure, patterns, and long-term strategy.
Meta-skill for understanding and customizing Mindfold Trellis — the all-in-one AI workflow system for 11 AI coding platforms (Claude Code, Cursor, OpenCode, iFlow, Codex, Kilo, Kiro, Gemini CLI, Antigravity, Qoder, CodeBuddy). Documents the original Trellis system design including architecture, commands, hooks, multi-agent pipelines, monorepo support, and task lifecycle hooks. Use when understanding Trellis architecture, customizing workflows, adding commands or agents, troubleshooting issues, or adapting Trellis to specific projects. Modifications should be recorded in a project-local trellis-local skill, not here.
Use when designing software architecture for bioinformatics pipelines, defining data structures, planning scalability, or making technical design decisions for complex systems.
System Architect that creates parallelizable PRDs with junior-proof technical specs. Use when planning features, designing implementations, or when the user says 'plan', 'architect', 'design', or 'PRD'. Outputs PRDs organized in Priority groups where tasks within each group can be executed in parallel by independent dev subagents (ralph). Each user story includes file ownership, technical specs, and acceptance criteria detailed enough for a Sonnet-class model to implement without clarification.
Create system architecture diagrams using Mermaid, PlantUML, C4 model, flowcharts, and sequence diagrams. Use when documenting architecture, system design, data flows, or technical workflows.
Use when complex systems need visual documentation, mapping component relationships and dependencies, creating hierarchies or taxonomies, documenting process flows or decision trees, understanding system architectures, visualizing data lineage or knowledge structures, planning information architecture, or when user mentions concept maps, system diagrams, dependency mapping, relationship visualization, or architecture blueprints.
Create excellent technical documentation with Mermaid diagrams. Use when documenting code architecture, API flows, database schemas, state machines, system design, or any technical concept that benefits from visual diagrams. Also use when asked to explain code, create documentation, write README files, or document how systems work.
Generates architecture diagrams from code, infrastructure, or descriptions. Use when user asks to visualize, diagram, or document system architecture.
Consult this skill when designing client-server systems or API architectures. Use when traditional web/mobile applications with centralized services, clear separation between client and server responsibilities needed. Do not use when selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: peer-to-peer dominates - consider dedicated P2P patterns.
Generate comprehensive C4 architecture documentation for an existing repository/codebase using a bottom-up analysis approach.
Technical implementation planning and architecture design. Capabilities: feature planning, system architecture, technical evaluation, implementation roadmaps, requirement breakdown, trade-off analysis, codebase analysis, solution design. Actions: plan, architect, design, evaluate, breakdown technical solutions. Keywords: implementation plan, technical design, architecture, system design, roadmap, requirements analysis, trade-offs, technical evaluation, feature planning, solution design, scalability, security, maintainability, sprint planning, task breakdown. Use when: planning new features, designing system architecture, evaluating technical approaches, creating implementation roadmaps, breaking down complex requirements, assessing technical trade-offs.
Analyzes events through computer science lens using computational complexity, algorithms, data structures, systems architecture, information theory, and software engineering principles to evaluate feasibility, scalability, security. Provides insights on algorithmic efficiency, system design, computational limits, data management, and technical trade-offs. Use when: Technology evaluation, system architecture, algorithm design, scalability analysis, security assessment. Evaluates: Computational complexity, algorithmic efficiency, system architecture, scalability, data integrity, security.