ss7172/graph-agents-cli

This skill should be used when the user wants to "deploy an agent", "deploy to Kubernetes", "deploy to our cluster", "set up CI/CD", "set up Argo CD", "configure secrets", "rotate a key", "promote to production", "check cluster prerequisites", "deploy to kind/k3s/minikube", "deploy air-gapped", or "troubleshoot a deployment". Covers the deployment modes (direct local-load, direct registry, helm-push, argocd), the dev/staging/ prod environments, the secrets procedure and rotation, the Argo CD PR flow and the single production merge gate, the required GitHub environment and branch-protection settings, infra check, local-load dev clusters, and the disconnected profile. Part of the graph-agents-cli skills suite. Do NOT use for agent code (graph-agents-cli-langgraph-code), evaluation (graph-agents-cli-eval), scaffolding (graph-agents-cli-scaffold), or tracing (graph-agents-cli-observability).

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "write an eval dataset", "add an eval case", "analyze eval failures", "compare eval results", "set a quality threshold", "why did eval exit 1", or "upload evals to LangSmith". Covers the enforceable eval gate (one rule, case statuses, exit codes), the dataset schema, deterministic expect checks, judge and quality metrics, the local-versus-disconnected distinction, and eval submit. Applies to any graph-agents-cli project. Do NOT use for agent code (graph-agents-cli-langgraph-code), deployment (graph-agents-cli-deploy), or scaffolding (graph-agents-cli-scaffold).

This skill should be used when the user wants to "write agent code", "build an agent with LangGraph", "add a tool", "add a node to the graph", "use a checkpointer", "stream events", "add human-in-the-loop", "add a subgraph", "switch the model provider", "implement the auth policy", "call an external API from a tool", or needs LangGraph and LangChain patterns for a graph-agents-cli project. Covers create_agent and StateGraph, tools with the API_CALLS declaration, memory vs postgres checkpointers and thread_id, streaming, interrupts, subgraphs, init_chat_model provider switching, the fake provider for tests, the auth policy adapter, the API client and api-policy.yaml, and telemetry opt-in. Do NOT use for scaffolding (graph-agents-cli-scaffold), evaluation (graph-agents-cli-eval), or deployment (graph-agents-cli-deploy).

This skill should be used when the user wants to "set up tracing", "enable LangSmith", "send traces to our collector", "monitor my agent", "debug production traffic", "see what the agent sent to the model", "log prompts", or needs guidance on observability for a graph-agents-cli project. Covers the TRACING_ENABLED opt-in, the TRACE_CAPTURE metadata versus full policy, LangSmith versus OTLP, the hashed principal id, run records, and what is never captured by default. Part of the graph-agents-cli skills suite. Do NOT use for deployment (graph-agents-cli-deploy) or agent code (graph-agents-cli-langgraph-code).

This skill should be used when the user wants to "create an agent project", "start a new LangGraph project", "build me a new agent", "scaffold a project", "add Kubernetes deployment", "add CI/CD to my project", "add Argo CD", "enhance my project", or "upgrade my project". Part of the graph-agents-cli skills suite. Covers graph-agents-cli create, scaffold enhance, and scaffold upgrade with every flag, the valid runtime x checkpointer x target combinations, prototype semantics, the registry default, the authentic-baseline rule for upgrade, and the files upgrade never touches. Do NOT use for writing agent code (graph-agents-cli-langgraph-code) or deployment operations (graph-agents-cli-deploy).

This skill should be used when the user wants to "develop an agent", "build an agent with LangGraph", "build a LangGraph agent", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent to Kubernetes", "monitor an agent", or needs the graph-agents-cli development lifecycle and coding guidelines. Entrypoint for building LangGraph agents with graph-agents-cli. Always active: provides the full workflow (understand, scaffold, build, evaluate, deploy, observe), process deference to a project's declared process, the spec-before-code gate, code preservation rules, the never-change-the-model rule, human approval before deploy, and the 3-strikes loop breaker.