JP's signature red-team pass — "how would I break this?" Argue against your own approach before proceeding. Trigger on any high-stakes decision, architecture choice, or before marking work complete.
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Google ADK (Agent Development Kit) orchestration patterns — boundaries, agent composition, and tool seams. Trigger when designing or reviewing multi-agent systems built on ADK. Authoritative source: adk.dev.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
ADK is a mental model for agent composition, not a framework to learn. The patterns transfer to any orchestration foundation.
This skill covers how to think about agent boundaries, orchestration topology, and tool seams using Google ADK principles. It is not a tutorial on SDK methods — the official docs at adk.dev own that. This skill covers the architecture of agent systems.
Verify current ADK documentation — before writing any agent topology or referencing API surface, fetch the latest docs from adk.dev. ADK evolves; training data lags.
Define agent responsibilities first — each agent in the system must have:
Choose the orchestration topology:
| Topology | When to use | Trade-off |
|---|---|---|
| Supervisor → Worker | Audit trails required; routing logic is complex | Adds latency; supervisor is a bottleneck |
| Sequential pipeline | Tasks are strictly ordered; each step feeds the next | Simple but no parallelism |
| Parallel fan-out | Independent sub-tasks that merge at a synthesis step | Fast; coordination overhead at merge |
| Peer-to-peer | Speed over governance; tasks are loosely coupled | Hard to audit; compliance risk |
Design the tool seams — tools are the boundary between an agent and the external world. Each tool should:
Plan for agent failure — every agent in the graph must have a declared failure behaviour: retry, escalate to supervisor, return partial result, or halt. Unhandled agent failure silently corrupts downstream output.
Add observability at the boundary — log every agent invocation: agent name, input summary, output summary, latency, tool calls made. The agent graph is only debuggable if the boundary calls are visible.
Run the Adversarial Gate — before finalising the topology, invoke adversarial-gate on the design. Common failure modes: supervisor SPOF, context window overflow at the synthesis step, tool permission creep, silent agent loops.
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JP's signature red-team pass — "how would I break this?" Argue against your own approach before proceeding. Trigger on any high-stakes decision, architecture choice, or before marking work complete.
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Read-only SRE checkup of any GCP project: deterministic probes of the edge, Cloud Run services, 7-day error logs, Cloud Scheduler, alert policies and uptime checks, Secret Manager and IAM, the data stores and the machine's own scheduled jobs, audited into one fixed status table (LIVE / WARNING / RED / INCONCLUSIVE) with evidence, findings by severity, what could not be checked, and a single OVERALL line delivered as one notification. Parametrised by a per-project manifest, so the same routine runs on every project. Use when the operator says "cloud checkup", "SRE check", "is everything live", "what's healthy / warning / red", "any errors this week", "audit the infra", "weekly checkup", "set up the weekly checkup", before a deploy or demo, or after an incident. Cloud Run first; App Engine and GKE differ only in the serving probes.
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Cloud guardrails for any vendor workload — Google Cloud (GCP, Vertex AI, GKE), AWS (IAM, EKS, Bedrock), Azure (Entra ID, Policy, AKS), Alibaba Cloud (RAM, mainland/international residency). Enforces identity least-privilege, mechanical policy, data boundaries, residency, cost caps, network egress and observability, with official-source validation before any claim. Trigger on any cloud infrastructure design, review, Terraform plan, or LLM/agent deployment; the-architect routes here.
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LLM and cloud cost awareness — model tiering, token budgets, right-sizing, and when a cheaper model suffices. Trigger before finalising any architecture that calls LLMs, before scaling a workload, or when a cost estimate is needed.
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Challenge vision alignment, value, cost, risk and operating ownership at material scope or release decisions.
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Decompose an epic into atomic parallelizable tasks, route each to the right skill, and keep the four delivery records straight — issues, STATUS, ROADMAP, CHANGELOG. Use as a meta-router when several skills could apply, and as the baseline for how delivery state is recorded. Trigger at the start of any multi-track epic, when the skill count exceeds ~12, or when the records have drifted from reality.
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