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

Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds valuable behavior beyond that: it states the return payload (image plus caption/description/page metadata) and the error-record behavior with an `available_images` fallback listing nearest figures. This is rich, non-obvious context.

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?

Three sentences with no wasted words: the first states the core operation, the second the return shape, the third the failure/error behavior. The most important information is front-loaded and every sentence earns its place.

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?

For a single-parameter, read-only tool with strong annotations and full schema coverage, the description covers input provenance, return contents, and error behavior. Without an output schema, this is still enough for an agent to call the tool correctly and interpret likely outcomes.

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?

Schema coverage is 100% and the schema description already explains that `refs` must be opaque ref tokens and that non-image segments return an error record. The description adds provenance ('from search/lookup/get_segments') but does not materially deepen parameter semantics beyond the schema, so baseline 3 applies.

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 uses a specific verb and resource ('Fetch datasheet figure images (PNG/JPEG)') and clearly identifies the input as opaque `ref` tokens from search/lookup/get_segments. This distinguishes it from sibling tools, especially get_segments, by stating it returns image data rather than segments.

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 clearly implies when to use this tool: after obtaining `type='image'` ref tokens, and it warns that non-image refs produce an error record. It does not explicitly name sibling alternatives or state 'use X instead,' but the provenance and type condition give sufficient usage context.

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