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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Prompt Engineering & Structured Output	20%	- Tool-augmented prompting 1. Tool-use driven reasoning patterns 2. Validation and retry loops - Instruction design 1. Few-shot prompting strategies 2. Deterministic output formatting (e.g., JSON)
Agentic Architecture & Orchestration	27%	- Multi-agent orchestration 1. Parallel task decomposition 2. Coordinator / sub-agent patterns - Agentic loops & lifecycle design 1. Tool use loop execution (request → tool_use → result → next step) 2. Stop reason handling and control flow
Claude Code Configuration & Workflows	20%	- CI/CD and workflow integration 1. Command vs plan mode usage 2. Automated pipeline integration - Claude Code configuration 1. Project-level vs user-level configuration 2. CLAUDE.md hierarchy and scoping
Context Management & Reliability	15%	- System reliability 1. Error propagation handling 2. Escalation strategies (fail vs retry vs human) - Context window optimization 1. Managing long conversation degradation 2. "Lost in the middle" mitigation strategies
Tool Design & MCP Integration	18%	- Tool interface design 1. Clear tool descriptions and boundaries 2. Structured tool input/output schemas - Model Context Protocol (MCP) 1. Tool selection and routing strategies 2. MCP server integration patterns

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Reliable CCA-F Study Notes - Anthropic Trustworthy CCA-F Exam Content: Claude Certified Architect Foundations (CCA-F) Pass Certify

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q77-Q82):

NEW QUESTION # 77
In a hub-and-spoke multi-agent architecture, what is the best practice for passing context from the coordinator agent down to a specialized subagent?

A. Share the entire coordinator conversation history to ensure the subagent has maximum context.
B. Pass only the explicit context, findings, and parameters specifically relevant to that subagent's assigned subtask.
C. Subagents automatically inherit the coordinator's full context window, so no explicit passing is needed.
D. Grant the subagent access to a shared global state object where the coordinator writes its findings.

Answer: B

Explanation:
Subagents do not automatically inherit parent context. Context isolation is a core principle in multi-agent orchestration. A subagent should only be passed explicit, relevant context specific to its task. Sharing the full coordinator history wastes tokens, causes context pollution, and degrades subagent performance.

NEW QUESTION # 78
After integrating a local MCP server providing code analysis tools (analyze_dependencies, find_dead_code, calculate _complexity), you verify the server is healthy and tools appear in the tools/list response. However, you observe that the agent consistently uses Grep to search for import statements instead of calling analyze_dependencies -even when users explicitly ask about "code dependencies." Examining tool definitions reveals:
MCP: analyze_ dependencies - "Analyzes dependency graph"
Built-in: Grep - "Search file contents for a pattern using regular
expressions. Returns matching lines with line numbers and surrounding
context."
What's the most effective approach to improve the agent's selection of MCP tools?

A. Split analyze_dependencies into granular tools ( list_imports, resolve_transitive_deps, detect_circular_deps) so each has a focused purpose less likely to overlap with Grep.
B. Expand MCP tool descriptions to detail capabilities and outputs - e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
C. Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.
D. Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.

Answer: B

Explanation:
Claude selects tools primarily from their names and descriptions. A specific description distinguishing dependency-graph analysis-including direct imports, transitive dependencies, and cycles-from simple text search makes analyze_dependencies the clearer choice.

NEW QUESTION # 79
A custom subagent named security-reviewer is defined in . claude/agents/. How does this subagent gain access to a project's deployed skills?

A. The subagent must execute the /load_skills command upon initialization.
B. Subagents automatically inherit all skills currently loaded by the main coordinator agent.
C. Built-in explorer agents cascade all available workspace skills to newly spawned subagents.
D. Skills must be explicitly listed in the skills field of the custom subagent's markdown definition.

Answer: D

Explanation:
Subagents start with a clean context and do not automatically inherit skills from the parent or main conversation. To grant a custom subagent access to skills, they must be explicitly listed in the 'skills' field of the subagent's configuration frontmatter.

NEW QUESTION # 80
When providing Claude with a 50-page document, you notice it accurately recalls details from the first and last pages but misses a critical instruction buried on page 25. What is this phenomenon called?

A. The "lost in the middle" effect
B. Attention dilution
C. Context truncation
D. Progressive summarization

Answer: A

Explanation:
The "lost in the middle" effect describes how models reliably process information at the beginning and end of long inputs but may omit findings or instructions buried in middle sections.

NEW QUESTION # 81
You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
An engineer asks your agent to identify untested code paths in a legacy payment processing module spanning 45 files. After reading the first 8 source files, the agent's responses are becoming noticeably less accurate - it's forgetting previously discussed code patterns and hasn't yet located all test files or traced critical payment flows. What's the most effective approach to complete this investigation?

A. Switch to using Grep to search for specific function names instead of reading full files, reducing the content loaded into context for remaining exploration.
B. Clear context with /clear, then selectively re-read only the most critical files discovered so far, writing key findings to a scratchpad file that persists between context resets.
C. Document all current findings in a summary report, clear context completely, then use that report as the sole reference for continuing the investigation.
D. Spawn subagents to investigate specific questions (e.g., "find all test files for payment processing," "trace refund flow dependencies") while the main agent coordinates findings and preserves high-level understanding.

Answer: D

Explanation:
Subagents isolate detailed exploration in separate context windows and return concise findings to the main agent. This prevents further context degradation while preserving high-level coordination across test discovery and payment-flow tracing.

NEW QUESTION # 82
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