dataverse_get_import_job

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnly, idempotent, non-destructive. Description adds behavioral details: mentions exclusion of large 'data' column by default, conditional retrieval via include_data, and specific error code 0x8004F037. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise (7 lines) and well-structured: first sentence states purpose, second lists return fields, third explains include_data, fourth links to sibling tools, fifth details error diagnostics. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's purpose (single record retrieval) and the presence of an output schema, the description covers all necessary aspects: return fields, optional data inclusion, error code clues, and preconditions. No gaps identified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides detailed descriptions for all three parameters (dataverse_url, import_job_id, include_data). The tool description adds no new semantic information beyond what the schema contains. Baseline 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Retrieve a single importjob record by its GUID to check import progress.' Distinguishes from sibling tools like dataverse_list_import_jobs (list) and dataverse_import_solution (start) by explicitly referencing them as prerequisites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises when to use this tool (check import progress) and directs the user to dataverse_import_solution or dataverse_stage_and_upgrade_solution to obtain the import_job_id. Also describes include_data usage for failure diagnosis.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.