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| Section | Weight | Objectives |
|---|
| Tools and MCPs | 10.6% | - Tool Development and Integration
- 1. Handle tool schemas, invocation, and tool-use results
- 2. Design and implement custom tools for Claude applications and agents
- Model Context Protocol
- 1. Build and integrate MCP servers
- 2. Apply MCP concepts and patterns for connecting models to external capabilities
|
| Prompt and Context Engineering | 11% | - Context Engineering
- 1. Apply context management strategies for agents and long-running workflows
- 2. Manage context windows and application context
- Prompt Engineering
- 1. Design prompts appropriate to application requirements
- 2. Apply prompting techniques to improve reliability and output quality
|
| Agents and Workflows | 14.7% | - Agent Architecture and Tradeoffs
- 1. Evaluate tradeoffs between agentic approaches and traditional workflows
- 2. Select appropriate agent architectures and patterns
- Subagents and Agentic Frameworks
- 1. Use subagents and coordinate multi-agent workflows
- 2. Apply appropriate agentic frameworks and orchestration patterns
- Claude Agent SDK and Agent Loops
- 1. Implement and manage custom agent loops
- 2. Build and configure agents using the Claude Agent SDK
|
| Model Selection and Optimization | 16.8% | - Performance and Cost Optimization
- 1. Apply prompt caching and other cost optimization techniques
- 2. Use batching and other approaches to improve efficiency
- Model Selection
- 1. Evaluate quality, latency, capability, and cost tradeoffs
- 2. Select appropriate Claude models for task requirements
|
| Security and Safety | 8.1% | - Secure Application Design
- 1. Apply secure-by-design practices to Claude-powered applications
- 2. Protect sensitive data and manage access appropriately
- Safety and Guardrails
- 1. Implement safety controls and guardrails
- 2. Use hooks and other mechanisms to enforce application controls
|
| Claude Code | 3.1% | - Claude Code Configuration and Usage
- 1. Use CLAUDE.md and project configuration
- 2. Configure settings and development environments
- 3. Use Skills, plugins, and Claude Code capabilities effectively
|
| Applications and Integration | 33.1% | - Claude API and Client SDKs
- 1. Integrate applications with the Claude API and supported client SDKs
- 2. Construct and process API requests and responses
- 3. Implement streaming and handle API errors
- Application Development and Integration
- 1. Handle multimodal and structured application inputs and outputs
- 2. Build and ship production-grade Claude-powered applications
- 3. Integrate Claude capabilities into existing software systems and workflows
|
| Eval, Testing, and Debugging | 2.6% | - Evaluation
- 1. Design and run evaluations for Claude-powered applications
- 2. Interpret evaluation results and improve application quality
- Testing and Debugging
- 1. Test Claude integrations and agentic systems
- 2. Diagnose and debug application, agent, and integration issues
|
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Anthropic Claude Certified Developer-Foundations Sample Questions (Q92-Q97):
NEW QUESTION # 92
A teammate has submitted a pull request that adds a Claude-powered feature to your service. The code works, but the prompt and model selection are hard-coded inline, error handling is missing, and there are no tests for the integration.
What would you request during code review?
- A. Request changes that move prompt and model configuration to a configurable location, add error handling for Claude API failures, and add tests for the integration.
- B. Request changes that move prompt and model configuration to a configurable location and add tests, treating the missing error handling as a follow-up release item.
- C. Approve the pull request and add the missing pieces yourself in a follow-up commit so the teammate can move on to other work immediately.
- D. Approve the pull request as-is, on the grounds that the feature works in the happy path and the missing pieces can be added in follow-up commits.
Answer: A
Explanation:
D is the only option that addresses all three identified production-readiness defects. The supplied Claude Developer item explicitly selects D. A functioning happy path is insufficient for a maintainable Claude integration.
Prompt and model selection are configuration concerns that will change as prompts are evaluated, model versions evolve, or environments require different behavior. They should therefore be separated from unrelated business logic rather than scattered as inline constants. Claude API failures must also be handled deliberately. Anthropic documents typed SDK exceptions and defined HTTP error categories, including invalid requests, authentication failures, rate limits, server errors, overload, and timeouts. The official SDKs additionally retry appropriate transient failures.
Tests are required to verify the integration boundary, including successful behavior, malformed or unexpected responses, API error handling, and critical user workflows. Approving code without those controls pushes known reliability debt directly into production.
A and B knowingly merge incomplete production behavior. C improves configuration and test coverage but leaves a known API-failure path unhandled.
Relevant Claude Developer topics: SW Eng Foundations, code review, separation of configuration, error handling, integration testing, API resilience, maintainability, and production readiness .
NEW QUESTION # 93
The team is debating whether to build a new capability as a custom tool or to use an existing built-in tool that nearly covers the use case but lacks one specific feature.
How would you decide?
- A. Evaluate whether the missing feature can be addressed by extending the built-in tool or warrants a custom tool, then choose accordingly.
- B. Review the built-in tool's documentation and assess whether its existing capabilities are sufficient to cover the use case without any modification or extension.
- C. Identify whether the team has previously built similar custom tools and use those precedents to determine which approach is more consistent with the existing codebase.
- D. Examine the custom tool option by scoping the implementation effort and determining whether the additional flexibility justifies the development and maintenance cost.
Answer: A
Explanation:
The supplied Claude Certified Developer Foundations material identifies A as the best answer. The decision should begin with the actual capability gap rather than a predetermined preference for built-in or custom tooling. If the existing capability can satisfy the requirement with a small supported extension or composition, using it avoids unnecessary implementation and maintenance. If the missing capability is fundamental, a custom tool becomes justified.
Anthropic's tool architecture explicitly supports both categories. Claude provides Anthropic-managed or predefined tools while also allowing developers to define custom tools for operations specific to their application. With a custom client tool, the application defines the contract and executes the operation before returning its result to Claude.
A is more complete than C because it evaluates both sides of the boundary : whether the existing mechanism can realistically meet the missing requirement and, if not, whether custom implementation is warranted. B prioritizes precedent over current requirements. D only determines whether the unmodified built-in tool is sufficient and does not address what to do when it is almost-but not entirely-sufficient.
Relevant Claude Developer topics: built-in tools, custom tools, capability-gap analysis, tool contracts, maintenance cost, extensibility, and agent construction decisions .
NEW QUESTION # 94
Your team uses Claude Code across multiple repositories. You want the team's rules and general coding standards to apply to all repositories, and other rules to apply only to specific repositories. The team is currently duplicating instructions across every repository's CLAUDE.md file.
How would you address this?
- A. Use a CLAUDE.md hierarchy that scopes general standards broadly and project-specific context within each repository's local CLAUDE.md.
- B. Stop using CLAUDE.md altogether and ask each developer to configure Claude Code manually for each project they work on.
- C. Move all instructions to a separate documentation site that developers consult during Claude Code sessions across all repositories.
- D. Use a single repository's CLAUDE.md as the central source of truth and link to it from every other repository's CLAUDE.md file.
Answer: A
Explanation:
B is directly supported by both the supplied examination source and Claude Code's configuration model. The source marks the hierarchical CLAUDE.md approach as correct. Claude Code supports instructions at multiple scopes, allowing broadly applicable standards to be separated from project-specific context rather than duplicated across every repository.
Anthropic documents several CLAUDE.md scopes. Organization-managed instructions can apply broadly; user-level instructions in ~/.claude/CLAUDE.md apply across a user's projects; project instructions in .
/CLAUDE.md or ./.claude/CLAUDE.md provide repository-specific architecture, conventions, commands, and workflows. Claude Code loads applicable files according to the directory hierarchy, allowing broad instructions and more specific local instructions to coexist.
This arrangement improves maintainability because common coding standards are defined once at the appropriate scope, while each repository retains only the context unique to that project. A documentation website does not automatically inject rules into Claude Code context. C creates inconsistent manual configuration. D improperly couples unrelated repositories to one repository's configuration.
Relevant Claude Developer topics: Confia Management, CLAUDE.md hierarchy, organization scope, user scope, project scope, repository configuration, instruction inheritance, and configuration reuse .
NEW QUESTION # 95
You are building a Claude application that needs to deliver model output to end users as it is generated, instead of waiting for the full response to complete.
The Claude API mechanism you would use is...
- A. Structured JSON output, which delivers responses only after the model has finalized the JSON shape across the entire response.
- B. Prompt caching, which speeds up the cost profile of future requests and does not affect the delivery timing of the first response.
- C. Streaming responses, which deliver tokens incrementally as the model generates them so users see output progressively.
- D. The Batch API, which delivers full responses after a delay suitable for non-interactive workloads.
Answer: C
Explanation:
Option B is the intended and technically correct answer. The supplied Claude Developer exam source selects streaming responses. Streaming allows the client application to begin receiving output before generation of the complete message has finished, reducing perceived latency for interactive user experiences.
Anthropic's official Messages API documentation states that setting stream: true causes responses to be delivered incrementally through Server-Sent Events (SSE) . Claude can stream text deltas as well as other event types, including structured tool-use and extended-thinking events where applicable. Anthropic's SDKs provide corresponding synchronous or asynchronous streaming helpers.
The application consumes events as they arrive, updates the UI progressively, and then handles the final event or stop reason when generation completes. This architecture is particularly useful for chat interfaces and other latency-sensitive interactive experiences.
A addresses output structure, not progressive transmission. C is designed for asynchronous, throughput- oriented processing rather than immediate user interaction. D reduces processing cost and latency for repeated prompt prefixes but does not itself turn a response into an incremental stream.
Relevant Claude Developer topics: Messages API, streaming, SSE, incremental tokens, latency, event handling, interactive applications, and API response mechanics .
NEW QUESTION # 96
You are designing a Claude application that will require structured JSON output for downstream processing.
The output schema is well-defined, and downstream systems will reject malformed JSON.
- A. Define a clear schema, structure the prompt to request output in that schema, and validate Claude's output against the schema before passing it downstream.
- B. Structure the prompt to request output in a schema that is described in plain English, with downstream systems parsing whatever shape Claude produces.
- C. Avoid structured output and use free-form text everywhere instead, on the grounds that free-form text is more flexible and handles edge cases better than structured schemas.
- D. Define a clear schema and structure the prompt to request output in that schema, with downstream systems handling any validation needed.
Answer: A
Explanation:
Option C establishes the strongest application boundary between probabilistic model generation and deterministic downstream processing. When another component requires JSON with a known contract, the application should explicitly define the expected structure and ensure that model output conforms to it before downstream execution. Anthropic's current Structured Outputs guidance states that structured outputs constrain responses to a specific schema and are intended to provide valid, parseable data for downstream processing. The current Claude API supports JSON Schema through output_config.format, while SDK helpers can additionally parse and validate returned data.
The underlying engineering principle remains the same even when structured-output enforcement is unavailable: never allow unvalidated model-generated structures to become trusted machine input. Option A provides insufficient contractual control. Option B defines the schema but pushes validation too late, increasing the probability that malformed or semantically invalid data reaches dependent components. Option D sacrifices machine reliability entirely.
Therefore, C correctly combines schema specification, explicit format guidance, and validation. This corresponds to Claude Developer topics covering structured outputs, defensive application design, schema validation, and reliable model-to-system interfaces. The question and options are reproduced from the supplied examination set.
NEW QUESTION # 97
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