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 explicitly states 'Pure function: no network calls, deterministic, free, unlimited within fair use', covering side effects, determinism, and usage limits. It also discloses the output structure (ready-to-publish text plus metadata) and that it's spec-correct, going well beyond what annotations would 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 front-loaded with the core purpose and flow, but is somewhat long due to tangential mentions of Shopify and x402 promotions. While these add context, they dilute conciseness. Every sentence is purposeful but could be tightened; still, it's well-organized and readable.

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 compensates by fully describing the return format and metadata. It covers the tool's role in the ecosystem (checkers, AI-readiness), provides behavioral guarantees, and includes usage examples. It's comprehensive for a tool with 3 parameters, 100% schema coverage, and no output schema.

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, but the description adds substantial meaning by mapping each parameter to its output role: summary becomes the blockquote, site_name the H1, and sections the H2s. It even explains the link bullet format, enriching the schema's descriptions with practical rendering context.

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 immediately states 'Generate a complete, spec-correct llms.txt file from structured input', with specific verb and resource. It explicitly identifies itself as the generator counterpart to this server's checkers, distinguishing it from sibling tools like agent_readiness_scan and check_wellknown_discovery.

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?

It clearly says when to use: 'the generator counterpart to this server's checkers' and notes that AI-readiness scanners (including agent_readiness_scan and check_wellknown_discovery on this server) check for llms.txt, implying you use this tool first. It also explains how to serve the output. However, it doesn't explicitly state when NOT to use it or list alternative generators, so it lacks explicit exclusions.

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