format_data_for_tool

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

Without annotations, the description reveals key behaviors: uses GPT-5-Medium for formatting, returns JSON strings or error objects, and does not raise exceptions directly. It does not mention potential latency or costs of the LLM call, but covers the core functionality.

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 with a clear docstring format (Args/Returns/Raises). It is mostly concise, though the opening sentence is somewhat redundant with the docstring.

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, the description covers the tool's purpose, parameters, and return format adequately for an agent to decide when to use it. It explains the meta-tool nature relative to sibling tools, though more details on LLM behavior could enhance completeness.

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 description's Args section adds meaning beyond the schema: tool_name as the target tool name, user_requirements as user intent, raw_data as optional raw data. This compensates for the 0% 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?

The description clearly states the tool formats data for another aerospace-mcp tool using GPT-5-Medium. It specifies the verb 'format' and the resource 'data for a specific aerospace-mcp tool', distinguishing it from siblings that perform direct calculations or analyses.

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 usage when raw data or requirements need formatting for an aerospace tool, but does not explicitly state when not to use it or provide alternatives. Context suggests it is a helper tool, but no direct exclusion criteria are given.

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