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

The description adds valuable behavioral context beyond the annotations: conversion can be lossy (e.g., JSON to CSV flattens nested structures), it requires a Bearer API key, billing is per input character, and HTTP 402 is returned on insufficient balance. These are exactly the kind of runtime traits an agent needs and that annotations do not provide.

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 two sentences, front-loaded with purpose and return value, then covers lossiness, auth, billing, and alternatives. Every clause earns its place and there is no fluff or tautology.

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 three-parameter transform tool with no output schema, the description covers operation, return value, lossy edge cases, auth requirements, billing behavior, and error condition. The only remaining details are in the schema, so the agent has everything needed to invoke it correctly.

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 100%, so the schema already documents all three parameters and their enums. The description does not add additional parameter-level meaning, such as format-specific edge cases or guidance on choosing `from_format`, so the baseline score of 3 is appropriate.

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: 'Transform text between JSON, YAML, TOML, and CSV formats.' It also names what the tool returns, which clarifies its function. It further distinguishes itself from siblings by explicitly directing comment-removal to `prune` and llms.txt generation to `generate`.

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 exclusions and alternatives: 'For removing comments use `prune`, for generating llms.txt use `generate`.' This tells the agent when not to use `convert` and what to use instead, which is explicit routing guidance beyond just naming the siblings.

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