Domain 1: Agent Architecture and Orchestration (27%)

1.1 Designing Agentic Loops for Autonomous Task Execution

Key knowledge:

• Agent loop lifecycle: send a Claude request, check stop_reason ("tool_use" vs "end_turn"), execute tools, return results for the next iteration
• Tool results are appended to the conversation history so the model can decide the next action
• Model-driven decision making (Claude chooses the next tool) vs hard-coded decision trees

Key skills:

• Flow control: continue the loop when stop_reason = "tool_use" and stop on "end_turn"
• Appending tool results to context between iterations
• Anti-patterns to avoid: parsing assistant text for completion, using arbitrary iteration limits as the primary stopping mechanism

1.2 Orchestrating Multi-agent Systems (Coordinator–Subagent)

Key knowledge:

• Hub-and-spoke architecture: the coordinator owns all inter-agent communication, error handling, and routing
• Subagents operate with isolated context—they do not automatically inherit the coordinator's history
• Coordinator responsibilities: task decomposition, delegation, result aggregation, dynamic selection of subagents
• Risk of overly narrow decomposition by the coordinator

Key skills:

• Split research coverage among subagents to minimize duplication
• Implement iterative refinement loops (coordinator evaluates synthesis and re-routes tasks)
• Route all communication through the coordinator for observability

1.3 Configuring Subagent Calls, Context Passing, and Spawning

Key knowledge:

• Task tool spawns subagents; the coordinator's allowedTools must include "Task"
• Subagent context must be explicitly included in the prompt; subagents do not inherit parent context
• AgentDefinition configuration: descriptions, system prompts, tool constraints
• Session management via fork_session for exploring alternatives

Key skills:

• Include full outputs from prior agents in the subagent prompt
• Use structured formats to separate data from metadata when passing context
• Spawn parallel subagents via multiple Task calls in a single coordinator turn
• Write coordinator prompts in terms of goals and quality criteria rather than step-by-step instructions

1.4 Implementing Multi-step Workflows with Enforcement and Handoff Patterns

Key knowledge:

• The difference between programmatic enforcement (hooks, preconditions) and prompt guidance for ordering a workflow
• When you need deterministic guarantees (e.g., identity verification before financial operations), prompts alone are insufficient
• Structured handoff protocols during escalation (customer ID, reason, recommended action)

Key skills:

• Programmatic preconditions that block downstream calls until prior steps are complete (e.g., block process_refund until get_customer returns a verified ID)
• Decompose multi-aspect customer requests into separate items
• Produce structured summaries when escalating to a human

1.5 Agent SDK Hooks for Intercepting Tool Calls and Normalizing Data

Key knowledge:

• Hook patterns (e.g., PostToolUse) to intercept tool results before the model consumes them
• Hooks that intercept outgoing calls to enforce compliance rules (e.g., block refunds above a threshold)
• Hooks provide deterministic guarantees vs prompt instructions that provide probabilistic compliance

Key skills:

• PostToolUse hooks for normalizing data formats (Unix timestamps, ISO 8601, numeric status codes)
• Interception hooks to block policy-violating actions with redirection to escalation
• Choose hooks over prompts when business rules require guaranteed compliance

1.6 Task Decomposition Strategies for Complex Workflows

Key knowledge:

• Fixed pipelines (prompt chaining) vs dynamic adaptive decomposition based on intermediate results
• Prompt chaining: sequential steps (analyze each file separately, then run an integration pass)
• Adaptive investigation plans that generate subtasks based on what was discovered

Key skills:

• Use prompt chaining for predictable multi-aspect reviews; use dynamic decomposition for open-ended investigations
• Split large code reviews into per-file analysis plus a separate cross-file integration pass
• Decompose open-ended tasks: map structure first, then build a prioritized plan

1.7 Session State, Resuming, and Forking

Key knowledge:

• --resume <session-name> to continue named sessions
• fork_session to create independent investigation branches from shared context
• The importance of informing the agent about file changes when resuming sessions
• A new session with a structured summary can be more reliable than resuming with stale results

Key skills:

• Use --resume to continue named investigation sessions
• Use fork_session to compare approaches in parallel
• Choose between resuming (context still current) vs starting a new session (results stale)