tldr_extract

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 describes what is extracted but does not disclose whether the tool is read-only, permissions required, or any side effects. Since it's an analysis tool, read-only is implied but not stated.

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 concise sentences with no wasted words. The action verb 'Extract' is front-loaded, and the purpose is immediately clear.

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 output schema, the description could mention the format of the analysis results or that it returns structured data. However, for a tool with 4 parameters primarily focused on extraction, the description provides reasonable context but lacks completeness about return values.

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 coverage is 100%, so baseline is 3. The description adds value by indicating the output includes classes, functions, etc., which aligns with the filter parameters. This contextualizes the parameters beyond their individual schema descriptions.

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 extracts full file analysis including classes, functions, methods, and imports, and specifies it's for deeply understanding a single file. This distinguishes it from sibling tools that focus on different aspects like architecture or calls.

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 some guidance ('Use to deeply understand a single file') but does not explicitly state when to use this tool over alternatives or when not to use it. Implicit usage is clear, but lacks exclusions.

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