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Agent skills
ai-agents

Topic: ai-agents

18,135 skills in this topic.

fetch-pr-feedback Fetch review comments from a PR and evaluate with receive-feedback skill
existential-birds/beagle 44
docling Docling document parser for PDF, DOCX, PPTX, HTML, images, and 15+ formats. Use when parsing documents, extracting text, converting to Markdown/HTML/JSON, chunking for RAG pipelines, or batch processing files. Triggers on DocumentConverter, convert, convert_all, export_to_markdown, HierarchicalChunker, HybridChunker, ConversionResult.
existential-birds/beagle 44
create-pr create a pull request with standardized description template
existential-birds/beagle 44
commit-push commit and push all local changes to remote repo
existential-birds/beagle 44
write-adr Generate ADRs from decisions made in the current session. Extracts decisions, confirms with user, writes MADR-formatted documents.
existential-birds/beagle 44
llm-judge Compare code implementations across 2+ repos using LLM-as-judge methodology with weighted scoring
existential-birds/beagle 44
brainstorm Turn ideas into comprehensive project specs through collaborative dialogue. Use BEFORE any planning or implementation — for new projects, features, or significant changes. Produces a system-agnostic spec document that can feed into any agentic workflow.
existential-birds/beagle 44
agent-architecture-analysis Perform 12-Factor Agents compliance analysis on any codebase. Use when evaluating agent architecture, reviewing LLM-powered systems, or auditing agentic applications against the 12-Factor methodology.
existential-birds/beagle 44
adr-writing Write Architectural Decision Records following MADR template. Applies Definition of Done criteria, marks gaps for later completion. Use when generating ADR documents from extracted decisions.
existential-birds/beagle 44
adr-decision-extraction Extract architectural decisions from conversations. Identifies problem-solution pairs, trade-off discussions, and explicit choices. Use when analyzing session transcripts for ADR generation.
existential-birds/beagle 44
12-factor-apps-analysis perform 12-Factor App compliance analysis on a codebase
existential-birds/beagle 44
12-factor-apps Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.
existential-birds/beagle 44
vercel-ai-sdk Vercel AI SDK for building chat interfaces with streaming. Use when implementing useChat hook, handling tool calls, streaming responses, or building chat UI. Triggers on useChat, @ai-sdk/react, UIMessage, ChatStatus, streamText, toUIMessageStreamResponse, addToolOutput, onToolCall, sendMessage.
existential-birds/beagle 44
pydantic-ai-tool-system Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.
existential-birds/beagle 44
pydantic-ai-testing Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.
existential-birds/beagle 44
pydantic-ai-model-integration Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.
existential-birds/beagle 44
pydantic-ai-dependency-injection Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.
existential-birds/beagle 44
pydantic-ai-common-pitfalls Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
existential-birds/beagle 44
pydantic-ai-agent-creation Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.
existential-birds/beagle 44
langgraph-implementation Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
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langgraph-code-review Reviews LangGraph code for bugs, anti-patterns, and improvements. Use when reviewing code that uses StateGraph, nodes, edges, checkpointing, or other LangGraph features. Catches common mistakes in state management, graph structure, and async patterns.
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langgraph-architecture Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
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deepagents-implementation Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
existential-birds/beagle 44
deepagents-code-review Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configuration and usage mistakes.
existential-birds/beagle 44