glm_generate_readme

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

No annotations exist, so the description must disclose behavior. It lists inputs and returns but does not clarify whether the tool writes the README.md to the working directory or simply returns generated content. This is a critical ambiguity given the working_directory parameter and the potential for side effects. The description doesn't cover permissions, reversibility, or error behavior.

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 concise and well-structured: a clear intro, a use-case line, a compact args list, and a returns line. Every sentence and detail earns its place with no redundancy. The formatting improves scannability.

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?

The description covers purpose, use case, parameters, and return value. However, it omits behavioral details such as whether it writes files, and doesn't address edge cases like missing working_directory or error conditions. Given that an output schema exists, the return description is useful but not sufficient to offset the missing operational context.

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%, so the description must compensate. It does so by naming each parameter and providing allowed values for style ('standard', 'comprehensive', 'minimal') and model ('haiku' or 'sonnet'). This adds meaningful information beyond the schema, though it doesn't explain what each style entails.

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 states a specific verb-resource pairing: 'Generate a README.md for a project using GLM.' This clearly distinguishes it from siblings like glm_summarize or glm_document, though it doesn't explicitly name them as alternatives. The combination of verb and specific resource makes the purpose unambiguous.

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 'Use for: creating project documentation, onboarding.' line provides a clear context in which to use this tool. It does not give explicit exclusions or name alternative tools for other documentation needs, but the stated use case is adequate.

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