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Found 15 Skills
Use when the user needs human-in-the-loop workflows in Airflow (approval/reject, form input, or human-driven branching). Covers ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator. Requires Airflow 3.1+. Does not cover AI/LLM calls (see airflow-ai).
Pre-ingestion verification for epistemic quality in RAG systems with 9-point verification and Two-Round HITL workflow
Use this skill when > Convert plans, specs, or requirements into independently-grabbable vertical slice issues. Each slice is a thin but complete end-to-end cut through all layers (schema, API, UI, tests). Classifies issues as HITL (human-in-the-loop) or AFK (automated, no human interaction needed).
LangGraph state-machine design and debugging for `StateGraph`, node/edge routing, checkpoints, `interrupt`, and HITL flows. Use when building or troubleshooting graph-based agents with conditional edges and thread state.
Design state machines, orchestration workflows, saga patterns, and resilience strategies for distributed systems, AI agents, and complex async processes. Use when asking for a workflow, state machine, orchestration design, saga, HITL checkpoint, or process resilience strategy.
CopilotKit integration patterns for providers, runtime wiring, `useCoAgent`, `useCopilotAction`, `useLangGraphInterrupt`, shared state, and HITL with LangGraph. Use when building agent-native product UX.
Knowledge base for designing, reviewing, and linting agentic AI infrastructure. Use when: (1) designing a new agentic system and need to choose patterns, (2) reviewing an existing agentic architecture ADR or design doc for gaps/risks, (3) applying the lint script to an ADR markdown file to get structured findings, (4) looking up a specific agentic pattern (prompt chaining, routing, parallelization, reflection, tool use, planning, multi-agent collaboration, memory management, learning/adaptation, MCP, goal setting, exception handling, HITL, RAG, A2A, resource optimization, reasoning techniques, guardrails, evaluation, prioritization, exploration/discovery). All rules and guidance are grounded in the PDF "Agentic Design Patterns" (482 pages).
Orchestrates the full journey from zero to a running Neo4j application. Executes 8 named stages in order: prerequisites → context → provision → model → load → explore → query → build. Each stage has its own reference file in references/ that the agent reads and follows when entering that stage. Supports both HITL and fully autonomous operation. Time budget: ≤15 min after DB is running (autonomous), ≤90 min total (HITL).
Create, share, view, comment on, edit, and run human-in-the-loop review loops over markdown documents via Proof, the collaborative markdown editor at proofeditor.ai ("Proof editor"). Use when the user wants to render or view a local markdown file in Proof, share markdown to get a URL, iterate collaboratively on a Proof doc, comment on or suggest edits in Proof, HITL a spec/plan/draft for human review, sync a Proof doc back to local, or work from a proofeditor.ai URL. Trigger on phrases like "view this in proof", "share to proof", "iterate with proof", or "HITL this doc", and on ce-brainstorm / ce-ideate / ce-plan handoffs for human review. Also match clear requests for a rendered/shared markdown review surface even if the user does not name Proof. Do not trigger on "proof" meaning evidence, math/logic proof, burden of proof, proof-of-concept, or bare "proofread this" requests where inline text review is expected.
Select the most appropriate pipeline for a user goal, lock it in `PIPELINE.lock.md`, and route checkpoint questions into `DECISIONS.md`. **Trigger**: pipeline router, choose pipeline, workflow selection, PIPELINE.lock.md, 选择流程. **Use when**: 用户目标/交付物不清晰，需要在 snapshot/survey/tutorial/systematic-review/peer-review 中选一个并设置最小 HITL 问题集。 **Skip if**: pipeline 已锁定（`PIPELINE.lock.md` 存在）且所需问题已回答/签字完成。 **Network**: none. **Guardrail**: 尽量一次性提问；信息不足就写 `DECISIONS.md` 并停下等待。
Guides edge and tactical autonomous systems—perception-planning-control under latency and safety constraints; behavior trees/state machines vs learned policies; human-on-the-loop; geofencing, no-strike rules, mission abort; sim and field testing; ROS2/middleware patterns; sensor fusion; degraded modes; autonomy audit logging. Use for UAS/autonomous stacks, safety rules, HITL, sim-to-field validation, fail-safe—not LLM products (ai-engineer), LLM red team (ai-redteam), safeguard serving (ml-infrastructure-engineer-safeguards), governance only (ai-risk-governance), MCU firmware without autonomy (embedded-real-time-software-engineer), plant PLC/DCS (control-software-developer), HIL security bench (hardware-in-the-loop-security-tester).
Use to summarize a recorded video via the LVS summarization microservice (HITL-gated) with a VLM fallback. Not for live RTSP captioning or incident-range reports.