Agent Building skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

langgraph-project-setup

Initialize and configure LangGraph projects with proper structure, langgraph.json configuration, environment variables, and dependency management. Use when users want to (1) create a new LangGraph project, (2) set up langgraph.json for deployment, (3) configure environment variables for LLM providers, (4) initialize project structure for agents, (5) set up local development with LangGraph Studio, (6) configure dependencies (pyproject.toml, requirements.txt, package.json), or (7) troubleshoot project configuration issues.

101 repo starsObserved in 6 repos

Agent Building

GitHub

langgraph-state-management

Design state schemas, implement reducers, configure persistence, and debug state issues for LangGraph applications. Use when users want to (1) design or define state schemas for LangGraph graphs, (2) implement reducer functions for state accumulation, (3) configure persistence with checkpointers (InMemorySaver/MemorySaver, SqliteSaver, PostgresSaver), (4) debug state update issues or unexpected state behavior, (5) migrate state schemas between versions, (6) validate state schema structure, (7) choose between TypedDict and MessagesState patterns, (8) implement custom reducers for lists, dicts, or sets, (9) use the Overwrite type to bypass reducers, (10) set up thread-based persistence for multi-turn conversations, or (11) inspect checkpoints for debugging.

101 repo starsObserved in 5 repos

Agent Building

GitHub

piflow-init

Pi Flow · INIT — create a structured workflow (a DAG of producer/verify nodes coordinating through the filesystem) and stand it up to run as a fleet of efficient pi agents (pi.dev / earendil-works/pi) driven by non-Claude coding-plan models, with Claude Code as the single console. The source of truth is a structured workflow TEMPLATE (`.piflow/<wf>/template/`); the `@piflow/core` SDK loads it into a WorkflowSpec and runs it one `pi` per node. INIT triages your starting point — PORT an existing Claude `.js`, IMPORT another engine's workflow (n8n/YAML/JSON), or COMPOSE fresh — then builds the template and the per-repo runner. Use to "create/author a pi-flow workflow", "stand up the runner in a repo", "port my Claude workflow to pi", "import an n8n workflow", "run my workflow on a non-Claude model", "pi-runner". To RUN/monitor an existing workflow use piflow-start; to IMPROVE one use piflow-enhance.

101 repo starsObserved in 2 repos

Agent Building

GitHub

braindb-agent

Persistent memory across sessions via the BrainDB agent. Use at conversation start and whenever you need to recall what you know about the user or save new information to long-term memory.