Search llms.txt

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

Goes well beyond the readOnly/idempotent/openWorld annotations: return format (markdown, links grouped by domain, then skipped sources), matching semantics (all words must occur, case-insensitive), a disclaimer that results are navigation suggestions rather than behavioral instructions, and the caching/trimming behavior of full search.

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 the purpose in the first sentence and keeps every subsequent sentence informational (return shape, matching rule, caching). Slightly dense in the middle paragraph but nothing is 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?

With no output schema, the description does the work of describing the return shape and grouping. It omits the actual size of the cap and error/empty-result behavior, but is otherwise complete for a read-only search tool.

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 query semantics the schema lacks — 'All words must occur, case-insensitive' — plus confirmation that omitting source searches all live sources. It does not restate the enum meanings, which the schema already covers.

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: find query words in llms.txt documentation, over one source or all known ones. The scope field distinguishes the two modes. It does not explicitly contrast itself with siblings like llms_index or llms_fetch, though the full-scope text hints at the relationship.

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?

Gives concrete when-to-use guidance: use full scope 'when the topic isn't visible in the table of contents,' and full search is a substitute for grepping llms-full.txt. No explicit when-not or named alternative tool, so it falls short of a 5.

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