get_workbook_image

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

No annotations are provided, so the description carries the full burden. It discloses key side effects: saving to the filesystem, scaling down images, compressing to a target size, and returning a file path with metadata. It doesn't mention overwrite behavior, permissions, or error handling, which is a gap for a tool that writes to disk, but the disclosed behaviors are useful and non-contradictory.

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?

The description is well-structured and concise, with four sentences that each add value: purpose, optimizing behavior, text detail rationale, and input requirements/naming convention. No filler or repetition, though it is slightly longer than necessary.

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 no annotations and no output schema, the description does a reasonable job: it explains the output (file path and metadata), the optimization behavior, and the required inputs. However, it lacks details on potential side effects (e.g., overwriting files), error scenarios, and doesn't fully cover all six parameters in the context of the tool's behavior. This makes it adequate but not complete.

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 schema has no top-level description coverage per context signals, so the description must compensate. It clarifies the workbookUrl as 'workbookRepoUrl from API responses' and explains view name normalization ('Dashboard 1' -> 'Dashboard1'). It also connects the 768px scaling to maxWidth and compression target to quality. However, it leaves maxHeight, format, and quality specifics largely to the schema, and the required parameter list includes defaults without behavioral guidance.

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?

The description clearly states the tool's function: it fetches, optimizes, and saves a Tableau Public visualization image. The verb 'fetches and optimizes' combined with the resource 'Tableau Public visualization image' distinguishes it from sibling tools like download_workbook_twbx or get_workbook_thumbnail, though it doesn't explicitly differentiate from get_workbook_thumbnail.

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?

The description implies when to use the tool by mentioning 'Preserves text detail important for dashboard analysis,' suggesting it's for cases where readable text matters. It also specifies required inputs (workbook URL and view name) and provides naming conventions. However, it does not explicitly state when to prefer this over alternatives like get_workbook_thumbnail, or mention any exclusions.

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