get_picture

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

With no annotations, the description carries the full burden, and it excels: it discloses that the payload is passed through unmodified (no decode/resize/truncate), warns about the potentially very large Base64 string, and enumerates the exact error messages for missing or oversized images. It also lists all response fields, giving the agent a complete behavioral picture.

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?

Though longer than average, every sentence earns its place: the core purpose is front-loaded, followed by a critical size caveat, response fields, pass-through behavior, and error cases. The structure is logical and skimmable, with no redundancy or filler.

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 tool with no output schema and no annotations, this description is exhaustive. It covers the return format, the size concern, the unmodified pass-through, and the exact error conditions. An agent has everything needed to call the tool correctly and handle the response, with no gaps.

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% — the only parameter, PERSONID, is already documented as required and described. The description adds no new parameter-specific meaning beyond what the schema provides; it mentions PERSONID in the response fields but not in a way that clarifies the input. Baseline 3 is appropriate because the schema already handles parameter semantics fully.

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 opens with a specific verb and resource: 'Returns a person's photo ID image', and names the underlying API it wraps (NBAPI GetPicture). It clearly distinguishes this from sibling tools like get_person, which returns person data rather than the image. The additional detail on response fields and error cases leaves no ambiguity about the tool's purpose.

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?

It explicitly advises preferring PICTUREURL when only file identification is needed, citing the large Base64 size, which is a concrete when-to-use alternative. Though no sibling tool serves the same function, the guidance about which response field to use is a clear usage directive. It also implies when to expect errors, adding context for the agent's decision-making.

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