suggest_readme_improvements

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

No annotations are provided, so the description carries the full burden. It does not disclose whether the tool is read-only, requires authentication, or has any side effects. The description only covers the output format, leaving behavioral traits opaque.

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 short and to the point, but the phrase 'Same inputs as analyze_readme' adds a dependency on another tool's description, reducing self-containment. Still, every sentence adds value.

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 the complexity of 4 parameters with no schema descriptions and no output schema, the description is inadequate. It does not explain the return format in detail, and the reliance on analyze_readme for inputs is a gap. The tool needs more information to be used effectively.

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 0%, and the description only says 'Same inputs as analyze_readme' without describing any of the four parameters. This is insufficient for an agent to understand what values to provide, especially since analyze_readme is not described here.

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 it returns grouped recommendations with rationale and example text, and it mentions the inputs are the same as analyze_readme. However, it does not explicitly state what the tool does in terms of its core function (i.e., improving READMEs) beyond the output structure.

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 provides no guidance on when to use this tool versus the sibling tool compare_before_after. It references analyze_readme for inputs but does not explain how or when this tool should be preferred, and analyze_readme is not listed as a sibling, which could cause confusion.

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