Generate an llms.txt skeleton

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

Adds substantial context beyond the annotations: up to 120 seconds runtime, crawl-delay respect, progress notifications per request with a progress token, cancellation stopping requests, and nothing written to disk. It also warns that site text is data, never instructions, which is valuable prompt-injection guidance not present in the structured fields.

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-loads what is built and from where, then layers exclusions, output behavior, timing, progress and safety in a compact sequence. Every sentence adds operational information with no filler.

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?

Covers source selection, exclusions, output shape (JSON, schemaVersion 1, matching the CLI), output destination (in the result, not on disk), runtime limits and cancellation. With no output schema, this is enough for an agent to call and interpret the tool correctly.

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 100%, so the schema fully documents url and maxPages (including bounds and default). The description doesn't add any parameter-level detail beyond what the schema already provides, so baseline 3 is appropriate.

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 resource: builds the skeleton of an llms.txt file, and names the two data sources (sitemap or home-page links). This clearly distinguishes it from siblings like llms_validate (validation) and robots_test (robots checks).

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?

Explains sources, exclusions (noindex, redirects, robots-blocked) and that the output is a draft to edit rather than a finished file. It doesn't explicitly say when to prefer it over llms_validate or check, but the context is clear from the described output.

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