Call a documented GPTProto API

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

Annotations already cover readOnly=false, openWorld=true, idempotent=false, and destructive=false. The description adds one genuinely useful behavioral detail: official-compatible model fields have provider prefixes removed automatically. However, it does not disclose side-effect potential, response behavior, or how streaming/output_json alter results, so it only partially augments the 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?

Two dense sentences with no filler. The core action and the key automatic transformation are front-loaded, and every clause adds information needed to use the tool or understand its behavior.

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?

This is a high-complexity tool with 11 parameters, nested object types, no output schema, and non-trivial behaviors like streaming and output selection. The description does not explain required parameters, supported methods, return format, or the role of output_json, and relies too heavily on prior familiarity with the CLI 'gptproto request'.

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 description coverage is only 27%, which is low, so the description needed to compensate by explaining the many parameters. It mentions 'JSON, multipart, header, and query fields' conceptually, which maps loosely to body/form/files/headers/query, but it does not explain required fields method and path, the meaning of allow_review, label, stream, or output_json, or how they interact.

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?

States the specific verb 'call' and the resource: a relative method/path published by gptproto_model_describe. It also distinguishes itself from the sibling describe tool by making clear it is the invocation counterpart, and the phrase 'MCP equivalent of `gptproto request`' anchors its intent unambiguously.

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 gives clear context that this tool is used for calling methods/paths previously discovered via gptproto_model_describe. It does not explicitly list exclusions or alternatives, but the 'published by gptproto_model_describe' dependency makes the intended workflow reasonably clear.

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