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| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering & Structured Output | 20% | - Prompt design
|
| Context Management & Reliability | 15% | - Context handling
|
| Agentic Architecture & Orchestration | 27% | - Agentic architecture patterns
|
| Tool Design & MCP Integration | 18% | - Tool integration
|
| Claude Code Configuration & Workflows | 20% | - Claude Code
|
Was ist Ihr Traum? Wünschen Sie nicht, in Ihrer Karriere großen Erfolg zu machen? Die Antwort ist unbedingt ,,Ja". So müssen Sie ständig Ihre Fähigkeit entwickeln. Wie können Sie Ihre Fähigkeit entwickeln, wenn Sie in der IT-Industrie arbeiten? Teilnahme an den IT-Zertifizierungsprüfungen und Erhalten der Zertifizierung ist eine gute Methode, Ihre IT-Fähigkeit zu erhöhen. Jetzt, Anthropic CCAR-F Prüfung ist eine sehr populäre Prüfung. Wollen Sie das CCAR-F Zertifikat bekommen? So melden Sie sich an der Anthropic CCAR-F Prüfung an und ITZert kann Ihnen helfen, deshalb sollen Sie sich nicht darum sorgen.
96. Frage
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, and Glob-and integrates with Model Context Protocol (MCP) servers.
Engineers frequently ask the agent to cross-reference code changes with Jira tickets during reviews- checking ticket descriptions, acceptance criteria, and recent comments. This currently requires manually copying and pasting content into conversations. The team wants the agent to access this standard Jira ticket data directly.
What is the most effective approach?
Antwort: D
Begründung:
Option D uses the established integration mechanism without creating unnecessary infrastructure. Anthropic's Claude Code MCP documentation specifically recommends connecting an MCP server when users repeatedly copy information from an external system, such as an issue tracker, into conversations. Once connected, the server exposes Jira operations through named, schema-defined tools that Claude can discover and invoke directly. This allows the agent to retrieve ticket descriptions, acceptance criteria, comments, and metadata while preserving the server's authentication and access controls.
Option A exposes authentication details to shell commands and requires the agent to construct requests and parse responses repeatedly. Option B is justified only when no existing server provides the required capabilities or the workflow requires highly specialized operations. The question requires standard Jira information, so building and maintaining another server is unnecessary. Option C creates stale, manually synchronized copies that lose permissions, current comments, and authoritative ticket state. The team should therefore select a trusted Jira MCP implementation, configure appropriate read-only scopes where possible, and verify its tool descriptions and data-access boundaries before enabling it.
97. Frage
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's exploration subagent spent 30 minutes analyzing a legacy payment system, reading 47 files and documenting data flows. The session was interrupted when the engineer's connection dropped. While away, a teammate merged a PR that renamed two utility functions. The engineer wants to continue the same exploration.
What's the most effective approach?
Antwort: D
Begründung:
Resuming the existing subagent preserves the expensive investigative context: files already inspected, data- flow relationships, hypotheses, and intermediate conclusions. Anthropic documents that session history contains prompts, tool calls, tool results, and responses, allowing an interrupted investigation to continue with its prior analysis intact. ( https://code.claude.com/docs/en/agent-sdk/sessions ) Subagent transcripts also persist within their parent session and can be resumed after an interruption or restart. ( https://code.claude.com
/docs/en/agent-sdk/subagents?utm_source=chatgpt.com )
The engineer must nevertheless disclose the renamed utility functions. Anthropic explicitly distinguishes conversation persistence from filesystem persistence: resuming restores what the agent previously knew, but it does not freeze or snapshot the repository. ( https://code.claude.com/docs/en/agent-sdk/sessions ) Without the update, the subagent may search for obsolete symbols, misinterpret broken references, or rely on stale file paths.
Option A loses the detailed transcript and replaces it with a necessarily compressed summary. Option B preserves context but conceals a material repository change. Option D duplicates a large transcript inside a new context, increasing token consumption without providing any advantage over native resume functionality.
The resumed prompt should name the renamed functions, identify the merge or affected files, and instruct the subagent to re-read only the changed areas before continuing its broader exploration.
Official references/topics: Session Resume; Persistent Subagent Transcripts; Repository Drift; Targeted Context Refresh.
98. Frage
After the web-search agent finds 25 sources containing 120,000 tokens of raw content, the document-analysis agent extracts 15,000 tokens of key insights, and the synthesis agent produces a coherent 3,000-token narrative draft, the coordinator must pass context to the report-generation agent for the final output with proper source citations. What context-passing strategy provides the best balance of completeness and efficiency?
Antwort: A
Begründung:
Option B gives the report generator the two forms of information it actually needs: a compact narrative containing the synthesized conclusions and precise evidence records supporting those conclusions. The source index should map claim identifiers to URLs, document locations, excerpts, and other provenance fields so citations can be generated and verified without reloading 120,000 tokens of raw material.
Anthropic's context-engineering guidance recommends distilling extensive subagent activity into high-signal summaries while preserving critical context and dependencies. Its research architecture similarly treats subagents as intelligent filters that compress large evidence collections before returning relevant findings to the coordinator.
Option A lacks sufficient location-level evidence for reliable citation verification. Option C postpones attribution until after drafting, when claim wording may no longer map cleanly to the original evidence.
Option D maximizes theoretical completeness but introduces extensive irrelevant material, higher token costs, slower processing, and greater context pollution. The synthesis draft plus a structured claim-to-source index maintains evidentiary completeness where it matters while eliminating intermediate searches, duplicate passages, and other low-value context.
99. Frage
You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
You've asked Claude Code to build a PDF report generation feature. The initial implementation queries the database correctly, but the output has formatting issues: table columns are too narrow causing content truncation, dates display without proper formatting, and page break handling is incorrect. You've noticed these issues interact--changing column widths affects how dates render, and page breaks depend on content height.
What's the most effective approach for iterating toward a working solution?
Antwort: D
Begründung:
The defects are coupled, so changing all three simultaneously would make it difficult to determine which modification caused an improvement or regression. Option C establishes a controlled sequence: correct the foundational column geometry, verify the resulting layout, format dates within the stabilized columns, and finally tune page breaks using the resulting content heights.
Anthropic recommends tight feedback loops and early course correction. It also advises supplying Claude with an executable or observable verification mechanism, such as a test, build result, generated fixture, or screenshot comparison. Claude can then make a focused change, inspect the output, and iterate until that specific condition is satisfied.
100. Frage
You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JSON schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your extraction system parses e-commerce product descriptions to extract specifications such as dimensions, weight, and materials into JSON. Despite having a well-defined schema, the model inconsistently extracts the materials field-sometimes returning "cotton blend," other times "Cotton/Polyester mix," and occasionally omitting the field when material information is clearly present in the source.
What is the most effective way to improve extraction consistency?
Antwort: C
Begründung:
Option D addresses the observed inconsistency at the model-behavior level. A schema can require that materials be a string, but it cannot teach Claude which lexical form the application considers canonical or demonstrate when a source phrase should populate the field. Anthropic identifies examples as one of the most reliable ways to steer output format, structure, and consistency, recommending several relevant and diverse examples that mirror the real task in its prompting best practices . Complete input-output pairs show both recognition and normalization: for example, a description containing "60% cotton, 40% polyester" can consistently map to the chosen "cotton/polyester blend" representation. They can also include difficult cases where material information is embedded indirectly in prose. Temperature zero reduces sampling variability but does not repair an underspecified transformation rule. A more capable model likewise lacks the missing formatting convention. Making the field required is dangerous because documents may legitimately omit materials; it can force unsupported values and increase hallucinations. Few-shot examples therefore supply the missing decision boundary while preserving truthful absence handling. The examples should be evaluated on held-out descriptions and supplemented by deterministic post-processing if downstream systems require an exact controlled vocabulary.
101. Frage
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