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

Annotations already establish readOnly, idempotent, openWorld and non-destructive, and the description still adds real behavioral facts: robots.txt is honored, noindex pages are skipped, at most 30 pages are read, output is format-checked before return, and 'Nothing is published.' The 'up to 30 pages' phrasing is slightly loose against max_pages default 20, but it is not a contradiction.

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?

Front-loaded with what gets produced (the file format) before the input modes, and every clause carries information. It is a dense paragraph rather than a broken-out structure, which costs a little scannability but wastes no sentences.

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?

With no output schema, the description implies the result is a validated llms.txt ready to be returned or used, which is enough for correct invocation. It stops short of describing the actual return payload shape, the one remaining detail an agent might want.

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 the baseline is 3, but the description adds genuine meaning the schema cannot convey: url and site_name/sections are alternative construction modes, and 'supplied fields override what is read from the site' defines precedence among them. That precedence rule is absent from the schema.

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?

States a specific verb and artifact ('Write an llms.txt file in the llmstxt.org format') and spells out the exact structure it produces. This is unambiguously distinct from siblings like validate_structured_data or audit_ai_readiness, which consume rather than generate artifacts.

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?

Clearly explains the two input modes: 'give url to build it from the live site' versus 'give site_name and sections to build it from your own facts,' plus the override rule when both are supplied. It gives strong in-tool routing guidance but never contrasts itself with the sibling tools, so the agent gets no external when-not guidance.

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