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102 questions selected from source version V9.02
CLAUDE CERTIFIED DEVELOPER
Question 1
Scenario: Developer Productivity with Claude 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 built-in tools (Read, Write, Bash, Grep, Glob) and
integrates with MCP servers. During a legacy payment module analysis, the coordinator first assigns one
subagent to map database tables and another to trace API callers. Both return useful findings. The
coordinator then invokes a planning subagent to propose a migration strategy, but the plan ignores the
database constraints and caller list already discovered, recommending changes that would break known
integrations.
What should you change to make this orchestration more reliable?
A. Replace the specialized subagents with one long-running generalist subagent that performs discovery and
planning together.
B. Instruct the planning subagent to infer missing dependencies from file names when prior findings are
unavailable.
C. Allow subagents to message each other directly so the planning subagent can request missing analysis
details.
D. Have the coordinator maintain shared investigation state and include relevant prior findings in each
subsequent subagent prompt.
Answer: D
Explanation
Coordinator-owned state is central to reliable multi-agent orchestration. In a coordinator-subagent pattern, the coordinator
decomposes work, collects results, and decides which findings must be supplied to later subagents so they can produce
grounded outputs.
The underlying principle is that subagents operate in isolated task contexts. They should not be designed as if they can
automatically see prior coordinator conversations or other subagents' outputs. The coordinator should maintain a structured
investigation state, such as discovered tables, caller lists, constraints, open questions, and confidence notes, then include
the relevant subset in each downstream prompt.
Letting subagents communicate directly weakens the hub-and-spoke architecture by hiding information flow from the
coordinator. Replacing specialists with one generalist can create context bloat and reduce the value of parallel specialized
analysis. Asking a planning subagent to infer missing dependencies from file names is especially risky because it substitutes
guesses for evidence.
For more on agent orchestration and subagent patterns, see the Agent SDK documentation and the Claude Code
Sub-agents documentation.
Page 2
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CLAUDE CERTIFIED DEVELOPER
Question 2
Scenario: Developer Productivity with Claude 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 built-in tools (Read, Write, Bash, Grep, Glob) and
integrates with MCP servers. An engineer asks the agent to explain how the "user export" capability works in
a legacy repository. The final answer confidently covers REST controllers and serializers, but misses
scheduled exports, admin-triggered jobs, and CLI invocations. Logs show every subagent completed
successfully; their prompts were "inspect export controller," "trace export API request," and "summarize
export endpoint tests.".
What should you change first to improve coverage on similar broad codebase questions?
A. Require each subagent to read every file matching export-related terms before returning any findings to
the coordinator.
B. Run a fixed pipeline that always invokes controller, database, CLI, worker, and test subagents for every
codebase query.
C. Strengthen the synthesis subagent prompt to infer missing workflows from naming conventions and
common framework patterns.
D. Revise coordinator planning to identify plausible entry points, then delegate distinct code areas to
subagents before synthesis.
Answer: D
Explanation
The root issue is the coordinator's task decomposition, not subagent execution. The subagents completed successfully, but
all assigned prompts focused on the REST API path, so the final answer missed other relevant workflows such as scheduled
jobs, admin actions, and CLI commands.
For broad codebase exploration, the coordinator should first reason about the possible surfaces where a capability may
appear, such as controllers, jobs, commands, tests, database models, and integrations. It can then delegate distinct areas to
specialized subagents and aggregate their findings into a complete explanation.
Asking synthesis to infer missing workflows is an anti-pattern because it encourages unsupported guesses. Having every
subagent read every matching file creates context bloat and attention dilution, while a fixed pipeline wastes work and ignores
the need for dynamic routing based on query complexity.
The underlying principle is that a coordinator-subagent architecture depends on the coordinator to preserve coverage and
routing discipline. Learn more about agent orchestration patterns in the Agent SDK documentation.
CLAUDE CERTIFIED DEVELOPER
Question 3
Scenario: Developer Productivity with Claude 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 built-in tools (Read, Write, Bash, Grep, Glob) and
integrates with MCP servers. An engineer asks the agent to investigate a production stack trace from an
unfamiliar legacy service. The trace contains the message "InvalidInventoryTransition" and references a
helper named validateTransition, but the repository has hundreds of source files and inconsistent directory
naming.
What should the agent do first to find the relevant implementation and usage sites efficiently?
A. Use Grep to search file contents for the error string and function names, then Read the matching files.
B. Use Bash to run ad hoc recursive shell commands, then paste the raw terminal output into context.
C. Use Read to load the entire module tree upfront, then ask the agent to infer all relevant references.
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Question 3 continued
D. Use Glob to list likely source files by extension, then Read each candidate file until the error appears.
Answer: A
Explanation
Grep is the right first tool when the agent needs to search file contents for known strings such as error messages, function
names, import statements, or identifiers. In practice, this lets the agent quickly identify candidate implementation and usage
sites, then use Read only on the files that matter.
The underlying principle is progressive codebase exploration: start with a narrow content search, then read the smallest
useful set of files to understand control flow and dependencies. This preserves context window capacity and avoids attention
dilution in large repositories.
Glob is useful for matching file paths, such as **/*.test.tsx, but it does not inspect file contents. Loading broad directory trees
with Read is an anti-pattern because it adds irrelevant material to context before the agent knows what matters. Using Bash
for ad hoc recursive searches can work in some environments, but raw terminal output is often noisy and less controlled than
the purpose-built code search tool.
For more on Claude Code and built-in development workflows, see Claude Code Overview.
CLAUDE CERTIFIED DEVELOPER
Question 4
Scenario: Multi-Agent Research System You are building a multi-agent research system using the Claude
Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes
documents, one synthesizes findings, and one generates reports. The system researches topics and
produces comprehensive, cited reports. During a run, the document-analysis subagent asks a source
retrieval MCP tool for the full text of a licensed market report. The backend rejects the request because the
license permits summaries and short excerpts only. Today the tool returns "access denied," causing the
coordinator to retry with paraphrased requests and then mark the source as unavailable.
What change would best let the agents handle this case correctly?
A. Return a successful empty result set so the synthesis agent can continue without exposing licensing
details.
B. Return isError true with errorCategory business, isRetryable false, and guidance to request summaries or
short excerpts instead.
C. Report a permission error and instruct the coordinator to escalate to infrastructure owners for immediate
credential repair.
D. Classify the rejection as transient and retry with backoff using progressively narrower full-text retrieval
queries.
Answer: B
Explanation
Structured MCP errors should give agents enough information to decide whether to retry, revise the request, explain a
limitation, or escalate. In this case, the backend is enforcing a licensing constraint: full-text retrieval is not allowed, but
summaries and short excerpts are allowed. Returning isError: true with errorCategory: "business", isRetryable: false, and a
human-readable explanation lets the coordinator avoid useless retries and choose an allowed retrieval strategy.
The key principle is distinguishing business rule violations from transient failures and permission problems. Transient retry
logic is appropriate for timeouts or temporary service unavailability, but it cannot overcome a stable contractual limitation.
Returning an empty successful result is an anti-pattern because it hides the difference between "no relevant source exists"
and "a relevant source exists but cannot be accessed in that form." Treating the case as credential repair also misroutes
recovery, since the issue is not missing authorization to perform an otherwise permitted action.
Learn more about MCP tool behavior in MCP Tools and Claude tool error handling patterns in Tool Use.
Page 4
102 questions selected from source version V9.02
CLAUDE CERTIFIED DEVELOPER
Question 1
Scenario: Developer Productivity with Claude 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 built-in tools (Read, Write, Bash, Grep, Glob) and
integrates with MCP servers. During a legacy payment module analysis, the coordinator first assigns one
subagent to map database tables and another to trace API callers. Both return useful findings. The
coordinator then invokes a planning subagent to propose a migration strategy, but the plan ignores the
database constraints and caller list already discovered, recommending changes that would break known
integrations.
What should you change to make this orchestration more reliable?
A. Replace the specialized subagents with one long-running generalist subagent that performs discovery and
planning together.
B. Instruct the planning subagent to infer missing dependencies from file names when prior findings are
unavailable.
C. Allow subagents to message each other directly so the planning subagent can request missing analysis
details.
D. Have the coordinator maintain shared investigation state and include relevant prior findings in each
subsequent subagent prompt.
Answer: D
Explanation
Coordinator-owned state is central to reliable multi-agent orchestration. In a coordinator-subagent pattern, the coordinator
decomposes work, collects results, and decides which findings must be supplied to later subagents so they can produce
grounded outputs.
The underlying principle is that subagents operate in isolated task contexts. They should not be designed as if they can
automatically see prior coordinator conversations or other subagents' outputs. The coordinator should maintain a structured
investigation state, such as discovered tables, caller lists, constraints, open questions, and confidence notes, then include
the relevant subset in each downstream prompt.
Letting subagents communicate directly weakens the hub-and-spoke architecture by hiding information flow from the
coordinator. Replacing specialists with one generalist can create context bloat and reduce the value of parallel specialized
analysis. Asking a planning subagent to infer missing dependencies from file names is especially risky because it substitutes
guesses for evidence.
For more on agent orchestration and subagent patterns, see the Agent SDK documentation and the Claude Code
Sub-agents documentation.
Page 2
,https://www.passcert.com/CCDV-F.html
CLAUDE CERTIFIED DEVELOPER
Question 2
Scenario: Developer Productivity with Claude 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 built-in tools (Read, Write, Bash, Grep, Glob) and
integrates with MCP servers. An engineer asks the agent to explain how the "user export" capability works in
a legacy repository. The final answer confidently covers REST controllers and serializers, but misses
scheduled exports, admin-triggered jobs, and CLI invocations. Logs show every subagent completed
successfully; their prompts were "inspect export controller," "trace export API request," and "summarize
export endpoint tests.".
What should you change first to improve coverage on similar broad codebase questions?
A. Require each subagent to read every file matching export-related terms before returning any findings to
the coordinator.
B. Run a fixed pipeline that always invokes controller, database, CLI, worker, and test subagents for every
codebase query.
C. Strengthen the synthesis subagent prompt to infer missing workflows from naming conventions and
common framework patterns.
D. Revise coordinator planning to identify plausible entry points, then delegate distinct code areas to
subagents before synthesis.
Answer: D
Explanation
The root issue is the coordinator's task decomposition, not subagent execution. The subagents completed successfully, but
all assigned prompts focused on the REST API path, so the final answer missed other relevant workflows such as scheduled
jobs, admin actions, and CLI commands.
For broad codebase exploration, the coordinator should first reason about the possible surfaces where a capability may
appear, such as controllers, jobs, commands, tests, database models, and integrations. It can then delegate distinct areas to
specialized subagents and aggregate their findings into a complete explanation.
Asking synthesis to infer missing workflows is an anti-pattern because it encourages unsupported guesses. Having every
subagent read every matching file creates context bloat and attention dilution, while a fixed pipeline wastes work and ignores
the need for dynamic routing based on query complexity.
The underlying principle is that a coordinator-subagent architecture depends on the coordinator to preserve coverage and
routing discipline. Learn more about agent orchestration patterns in the Agent SDK documentation.
CLAUDE CERTIFIED DEVELOPER
Question 3
Scenario: Developer Productivity with Claude 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 built-in tools (Read, Write, Bash, Grep, Glob) and
integrates with MCP servers. An engineer asks the agent to investigate a production stack trace from an
unfamiliar legacy service. The trace contains the message "InvalidInventoryTransition" and references a
helper named validateTransition, but the repository has hundreds of source files and inconsistent directory
naming.
What should the agent do first to find the relevant implementation and usage sites efficiently?
A. Use Grep to search file contents for the error string and function names, then Read the matching files.
B. Use Bash to run ad hoc recursive shell commands, then paste the raw terminal output into context.
C. Use Read to load the entire module tree upfront, then ask the agent to infer all relevant references.
Page 3
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Question 3 continued
D. Use Glob to list likely source files by extension, then Read each candidate file until the error appears.
Answer: A
Explanation
Grep is the right first tool when the agent needs to search file contents for known strings such as error messages, function
names, import statements, or identifiers. In practice, this lets the agent quickly identify candidate implementation and usage
sites, then use Read only on the files that matter.
The underlying principle is progressive codebase exploration: start with a narrow content search, then read the smallest
useful set of files to understand control flow and dependencies. This preserves context window capacity and avoids attention
dilution in large repositories.
Glob is useful for matching file paths, such as **/*.test.tsx, but it does not inspect file contents. Loading broad directory trees
with Read is an anti-pattern because it adds irrelevant material to context before the agent knows what matters. Using Bash
for ad hoc recursive searches can work in some environments, but raw terminal output is often noisy and less controlled than
the purpose-built code search tool.
For more on Claude Code and built-in development workflows, see Claude Code Overview.
CLAUDE CERTIFIED DEVELOPER
Question 4
Scenario: Multi-Agent Research System You are building a multi-agent research system using the Claude
Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes
documents, one synthesizes findings, and one generates reports. The system researches topics and
produces comprehensive, cited reports. During a run, the document-analysis subagent asks a source
retrieval MCP tool for the full text of a licensed market report. The backend rejects the request because the
license permits summaries and short excerpts only. Today the tool returns "access denied," causing the
coordinator to retry with paraphrased requests and then mark the source as unavailable.
What change would best let the agents handle this case correctly?
A. Return a successful empty result set so the synthesis agent can continue without exposing licensing
details.
B. Return isError true with errorCategory business, isRetryable false, and guidance to request summaries or
short excerpts instead.
C. Report a permission error and instruct the coordinator to escalate to infrastructure owners for immediate
credential repair.
D. Classify the rejection as transient and retry with backoff using progressively narrower full-text retrieval
queries.
Answer: B
Explanation
Structured MCP errors should give agents enough information to decide whether to retry, revise the request, explain a
limitation, or escalate. In this case, the backend is enforcing a licensing constraint: full-text retrieval is not allowed, but
summaries and short excerpts are allowed. Returning isError: true with errorCategory: "business", isRetryable: false, and a
human-readable explanation lets the coordinator avoid useless retries and choose an allowed retrieval strategy.
The key principle is distinguishing business rule violations from transient failures and permission problems. Transient retry
logic is appropriate for timeouts or temporary service unavailability, but it cannot overcome a stable contractual limitation.
Returning an empty successful result is an anti-pattern because it hides the difference between "no relevant source exists"
and "a relevant source exists but cannot be accessed in that form." Treating the case as credential repair also misroutes
recovery, since the issue is not missing authorization to perform an otherwise permitted action.
Learn more about MCP tool behavior in MCP Tools and Claude tool error handling patterns in Tool Use.
Page 4
