beagle

tag and push a release after the release PR is merged

create a release PR (auto-detects previous tag)

Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.

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.

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.

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.

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.

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.

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.

Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.

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.

Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.

Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.

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.

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.

Use when you need to mine a conversation, session transcript, or design discussion for architectural decisions before writing ADRs. Identifies problem-solution pairs, trade-off debates, technology choices, and explicit \"[ADR]\" tags. Triggers on \"what decisions did we make\", \"extract decisions from this chat\", \"find the choices in our discussion\", or \"summarize architectural decisions\". Also useful after long planning sessions to capture decisions that were made implicitly. Does NOT write ADR documents \u2014 use adr-writing or write-adr for that.

Use when writing or formatting an ADR document using the MADR template, applying Definition of Done (E.C.A.D.R.) criteria, or verifying ADR completeness. Triggers on \"write the ADR\", \"format as MADR\", \"check ADR quality\", \"mark gaps in ADR\". Also triggers when a decision has been extracted and needs to become a document. Does NOT extract decisions from conversations (use adr-decision-extraction) or orchestrate the full extract-confirm-write workflow (use write-adr).

Use when auditing an agent codebase against the 12-Factor Agents methodology, reviewing LLM-powered system architecture, or assessing agentic app compliance. Triggers on \"analyze agent architecture\", \"12-factor audit\", \"how compliant is this agent\", or \"evaluate this LLM app\". Also applies when comparing frameworks or planning agent improvements. Not for quick checklists \u2014 this performs deep per-factor codebase analysis with file-level evidence.

Use when the user wants a cited, structured read of local documents and project knowledge. Triggers on: \"analyze these docs\", \"scan my project for context\", \"read the docs folder\", \"summarize what's in .beagle/concepts/\", \"extract context from docs/\", \"what's in this folder\", \"go read everything in X and tell me what's there\". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups (\"find this function\", \"search the repo\"), web research (use web-research), LLM-as-judge evaluation (use llm-judge), or document editing (use humanize-beagle). Produces a written scan plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.

Use when the user has a fuzzy idea and wants to shape it into a concrete project spec before planning or building. Triggers on: \"brainstorm this\", \"I have an idea for...\", \"help me think through this project\", \"what should I build\", \"spec this out\". Also catches vague feature descriptions needing structured questioning to clarify scope. Does NOT write code, plan implementation, review strategy docs, or run strategy interviews \u2014 produces a WHAT/WHY spec through dialogue, not a HOW plan.

Use when comparing two or more code implementations against a spec or requirements doc. Triggers on \"which repo is better\", \"compare these implementations\", \"evaluate both solutions\", \"rank these codebases\", or \"judge which approach wins\". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality \u2014 use code review skills instead. Does NOT evaluate strategy docs \u2014 use strategy-review. Requires a spec file and 2+ repo paths.

Use when the user wants to pressure-test a product, internal-tool, or OSS concept against Amazon's Working Backwards PRFAQ gauntlet before committing to a spec. Triggers on: \"work backwards\", \"write a PRFAQ\", \"press release first\", \"is this idea worth building\", \"pressure-test this concept\", \"filter this before brainstorm\", \"is this a real product\". Also catches solution-first pitches (\"I want to build X that does Y\") and technology-first pitches (\"use AI to...\") that need customer-first filtering. Produces a binary pass/fail verdict, not a polished doc. Hardcore coaching — direct, skeptical, concrete. On pass, hands off to brainstorm-beagle with a concept brief. Does NOT write code, plan implementation, scaffold projects, or draft specs.

Use as the follow-up to brainstorm-beagle when a spec has an Open Questions section (or quietly carries latent gaps) that need closing before planning or implementation can begin. Triggers on: \"resolve the open questions\", \"close the gaps in this spec\", \"research the open items\", \"finalize my spec\", \"make this spec implementation-ready\", \"answer the TBDs\". Also triggers whenever the user points at a brainstorm-beagle spec and asks for research, proposals, or answers to unresolved items. Orchestrates parallel research subagents when available (falls back to inline sequential research otherwise), proposes answers one at a time for user approval, then rewrites the spec in place so it arrives at planning with no known gaps. Does NOT write code, design implementation, or create plans — it only produces a complete spec.

Use when the user wants to build or think through a strategy via guided conversation \u2014 for a company, product, team, career, or initiative. Triggers on \"help me figure out our direction\", \"what should we focus on\", strategic planning, competitive positioning, go-to-market strategy. Also catches indirect requests like prioritization struggles or \"we have too many priorities\". Does NOT review existing strategy documents (use strategy-review) or brainstorm project features (use brainstorm-beagle).