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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Product and Model Selection | 12% | - Match model capabilities to task requirements - Understand model differences and use cases - Select appropriate Claude product features |
| Topic 2: Configuration and Knowledge Management | 12% | - Manage knowledge sources and context - Maintain consistent system-level behavior - Configure Claude Projects with instructions |
| Topic 3: Troubleshooting and Optimization | 10% | - Identify causes of poor or unexpected outputs - Diagnose context and performance issues - Adjust prompts and configuration to improve results |
| Topic 4: Prompting and Task Execution | 14% | - Create effective prompts for business and technical tasks - Iterate prompts to improve output quality - Apply task decomposition to structure complex requests - Adapt prompting strategies by task type |
| Topic 5: Output Evaluation and Validation | 21% | - Evaluate outputs for accuracy, completeness, and consistency - Determine when human review is required - Detect hallucinations, biases, and inconsistencies - Apply fact-checking and validation methods |
| Topic 6: Workflow Integration and Solution Design | 16% | - Plan end-to-end Claude-augmented workflows - Design AI-assisted processes and solutions - Integrate Claude into existing business workflows |
| Topic 7: Governance, Risk, and Responsible Use | 15% | - Manage data sensitivity and privacy risks - Understand limitations and ethical boundaries - Apply responsible AI principles and policies |
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NEW QUESTION # 138
A Claude associate is evaluating whether to enable a Skill that was provided by an unfamiliar third party.
Which two checks best support a sound trust decision? (Select two.)
Answer: A,E
Explanation:
A Skill from an unfamiliar party must be treated as untrusted until its origin and behavior are reviewed.
Option A verifies provenance and confirms that the Skill is permitted by the organization's governance process. Option B applies least privilege by examining what the Skill can access or execute and determining whether those capabilities are necessary for its stated task.
Public availability, popularity, or favorable reviews do not establish security. A Skill can contain instructions, scripts, dependencies, external calls, or other resources capable of causing unintended actions or exposing data. Therefore, Options C and D substitute reputation for technical and organizational validation. Option E is also unsafe because Skills may execute code or access resources available in the surrounding environment; assumed workflow boundaries are not a reliable security control.
Anthropic warns that malicious or compromised Skills can create prompt-injection, unauthorized-access, and data-exfiltration risks. Its guidance instructs users to install Skills only from trusted sources and to inspect bundled files, scripts, dependencies, network calls, and requested operations before enabling them.
Organizational allowlists and permission reviews provide complementary controls: one establishes trust in the source, while the other limits what the Skill may do. Anthropic's Skill security guidance
NEW QUESTION # 139
A knowledge worker is preparing to use the Gmail connector with Claude for the first time.
Which statement most accurately describes the connector's behavior at the user level?
Answer: D
Explanation:
Option D best reflects the controlled, user-authorized behavior expected when Claude works with connected Gmail information. Claude can search and analyze emails that the authenticated user is already permitted to access. It can then use the retrieved information to summarize conversations, identify relevant details, or prepare a proposed reply. The user remains responsible for reviewing and sending that reply.
The connector does not independently authorize Claude to send routine messages merely because they appear low risk, so Option B assigns excessive autonomy. Option C incorrectly describes automatic inbox labeling as the connector's defining behavior. Option A correctly recognizes the read-oriented access model but understates Claude's usefulness: Claude can generate draft reply content even though the final communication remains under the user's control.
Connector access is also bounded by the permissions of the connected account. It does not grant Claude broader access than the user already possesses. This supports the principles of least privilege, explicit authorization, and human control over external actions. Before using the connector, the organization should also confirm that Gmail is an approved data source and that the emails involved are suitable for processing under its data-classification and privacy policies.
NEW QUESTION # 140
You are a project lead reviewing a teammate's habit of using the same prompt template for every task regardless of type.
Which feedback is most warranted?
Answer: A
Explanation:
Different tasks require different prompting structures, evidence, constraints, and evaluation methods. A research request should define research questions, source requirements, currency expectations, and citation rules. An analytical task should specify the decision to support, relevant data, assumptions, and comparison criteria. Drafting work requires audience, tone, purpose, structure, and length. Brainstorming normally benefits from broader exploration, diversity requirements, and delayed evaluation.
A reusable template can provide a useful baseline, but it should not remain unchanged when task characteristics differ. Options B, C, and D incorrectly assume that uniformity guarantees effectiveness. In practice, excessive rigidity can omit critical instructions or impose an inappropriate structure. A compliance report and an early-stage ideation exercise should not be prompted identically.
Anthropic's prompting documentation covers multiple techniques-including clear instructions, examples, role prompting, structured formats, prompt chaining, and success criteria-because no single technique is optimal for every workload. Anthropic's legal-summarization guidance also demonstrates that prompt details can be adjusted for different levels of technicality, verbosity, and structure. The project lead should therefore standardize reusable components while adapting task-specific objectives, inputs, constraints, and output formats. Anthropic's prompt-engineering overview
NEW QUESTION # 141
An operations assistant is redesigning a recurring data-processing workflow step to use Code Execution.
Which two design choices best support reliable integration? (Select two.)
Answer: B,E
Explanation:
Options A and E are correct because reliable automation requires controlled inputs and validated outputs.
Standardizing the expected input format reduces parsing failures, inconsistent field mappings, and uncontrolled variation between weekly runs. The integration should define required columns, data types, date formats, permitted null values, file naming conventions, and error-handling behaviour. This makes results comparable and supports repeatable testing.
Human verification remains necessary because successful code execution proves only that the program completed without a runtime error. It does not prove that the source data was correct, the implemented calculation matched the business requirement, or the result is operationally reasonable. A sanity check against an expected range, reconciled total, sample calculation, or known baseline helps detect silent logical and data- quality errors before downstream use.
Option B introduces avoidable variability and should instead be handled through standardized preprocessing or explicit adapters. Option C creates an undocumented interface that downstream consumers cannot reliably interpret. Option D confuses sandbox isolation and successful execution with result validation. Anthropic confirms that Code Execution can process files, perform calculations, and generate analytical outputs in a sandbox, but its outputs must still be evaluated against task-specific success criteria. See Anthropic's Code Execution documentation and evaluation guidance .
NEW QUESTION # 142
You are an operations assistant asking Claude to summarize 200 weekly metric records across multiple regions.
Which output format communicates the data most clearly?
Answer: C
Explanation:
Under the objective Organize and curate information for optimal outputs and select appropriate output formats , selecting the right presentation format is determined by data density, comparability, and target audience utility.
When dealing with a high volume of multi-variable quantitative data (such as 200 metric records across multiple regional cohorts), structured tabular formatting provides the highest visual scanability and cognitive efficiency. Organizing data into a Markdown table with uniform rows, standardized metric columns, and regional sorting (Option D) enables immediate horizontal and vertical cross-comparison, trend spot-checking, and rapid verification. In contrast, narrative prose, regional paragraph briefs, or unstructured bullet points (Options A, B, and C) obscure numerical trends, hide outliers, and create unnecessary reading overhead for operational consumers.
NEW QUESTION # 143
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