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Agent skills
agentic-ai

Topic: agentic-ai

3,764 skills in this topic.

component-refactoring Refactor high-complexity React components in frontend. Use when the user asks for code splitting, hook extraction, or complexity reduction, or when you come across a component that is too complex to understand and refactor it.
PageAI-Pro/ralph-loop 193
architecture-reviewer Use when making architectural decisions, planning features, designing new components, reviewing PRs, or validating that proposed changes align with Clean Architecture principles. Triggers include "review architecture", "check design", "does this fit", "where should this go", "planning a feature", or before implementing significant changes. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
cross-validate-artifacts Cross-validate documentation and artifacts across the codebase for consistency, conflicts, and contradictions. Use when users ask to "cross-validate", "validate docs", "check documentation consistency", "audit documentation", or find conflicts/contradictions in docs. Supports automatic fixing with "validate and fix" argument. Runs parallel subagents for efficient validation across categories (domain-models, agent-system, tech-stack, architecture, cli-commands). Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
mermaid-diagrams Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.
shep-ai/shep 126
react-flow React Flow (@xyflow/react) for workflow visualization with custom nodes and edges. Use when building graph visualizations, creating custom workflow nodes, implementing edge labels, or controlling viewport. Triggers on ReactFlow, @xyflow/react, Handle, NodeProps, EdgeProps, useReactFlow, fitView.
shep-ai/shep 126
shadcn-ui Provides complete shadcn/ui component library patterns including installation, configuration, and implementation of accessible React components. Use when setting up shadcn/ui, installing components, building forms with React Hook Form and Zod, customizing themes with Tailwind CSS, or implementing UI patterns like buttons, dialogs, dropdowns, tables, and complex form layouts.
shep-ai/shep 126
shep-kit:commit-pr Use when ready to commit, push, and create a PR with CI verification. Triggers include "commit and pr", "push pr", "create pr", "ship it", or when implementation is complete and needs CI validation. Watches CI and auto-fixes failures. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:fast-loop Use when the user wants rapid implementation iteration without tests, builds, or commits. Triggers include "fast loop", "fast iteration", "just code", "no tests", "iterate quickly", or when the user says they have a dev server running and want to check results manually. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:implement Validate specs and autonomously execute implementation tasks with status tracking. Use after /shep-kit:plan when ready to start implementation. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:merged Use after a PR has been merged to clean up. Switches to main, pulls latest, and deletes the local feature branch. Triggers include "merged", "pr merged", "cleanup branch", or after confirming a PR was merged. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
vercel-react-best-practices React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
shep-ai/shep 126
tsp-model Use when creating, modifying, or documenting TypeSpec domain models. Triggers include adding new entities, value objects, enums, extending base types, or when asked to create a "tsp model", "domain model", "entity", or work with files in the tsp/ directory. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep:ui-component Use when creating, modifying, or reviewing web UI components. Triggers include "new component", "add component", "create UI", "build a widget", "update component", working with files in src/presentation/web/components/, or when the user asks to build any React component for the web UI. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:status Quick feature status and "what to do next" guide. Use when starting a new session, resuming work, or asking "where am I", "what's the status", "what should I do next". Gives a zero-to-hero walkthrough of the current feature branch. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:research Use after /shep-kit:new-feature to analyze technical approach, evaluate libraries, document decisions. Triggers include "research", "technical analysis", "evaluate options", "which library", or explicit /shep-kit:research invocation. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:plan Use after /shep-kit:research to create implementation plan and task breakdown. Triggers include "plan", "implementation plan", "break down tasks", "create tasks", or explicit /shep-kit:plan invocation. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:parallel-task Use when a task can be worked on in isolation alongside other work. Creates a git worktree in .worktrees/ with a unique branch for parallel development. Triggers include "parallel task", "worktree", "work in isolation", or explicit /shep-kit:parallel-task invocation. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:new-feature-fast Fast-track feature creation that collapses new-feature, research, and planning into a single autonomous pass. Produces all spec YAMLs (spec, research, plan, tasks, feature) in one go with minimal user interaction. Triggers include "quick feature", "fast feature", "rapid spec", or explicit /shep-kit:new-feature-fast invocation. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
shep-kit:new-feature Use when starting any new feature, functionality, or enhancement. Triggers include "new feature", "start developing", "add functionality", "implement X", or explicit /shep-kit:new-feature invocation. Creates spec branch and scaffolds specification directory. Part of the Shep autonomous SDLC platform — https://shep.bot
shep-ai/shep 126
recall Reconstruct and narrate the current development context from contextual commits. Run at session start, when resuming work, or when switching branches. Produces a brief, conversational summary of where things stand.
berserkdisruptors/contextual-commits 125
contextual-commit Write contextual commits that capture intent, decisions, and constraints alongside code changes. Use when committing code, finishing a task, or when the user asks to commit. Extends Conventional Commits with structured action lines in the commit body that preserve WHY code was written, not just WHAT changed.
berserkdisruptors/contextual-commits 125
AgentDB Performance Optimization Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
spencermarx/open-code-review 126
AgentDB Memory Patterns Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
spencermarx/open-code-review 126
AgentDB Learning Plugins Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
spencermarx/open-code-review 126