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

Annotations already cover readOnly/openWorld/idempotent, so the safety profile is known. The description adds useful behavioral nuance beyond that: the HEAD-probe caveat for llms-full.txt existence and the fact that all attempted rungs are returned for diagnosability. This goes beyond what annotations express, though it stops short of describing edge cases like network failures or malformed llms.txt files.

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 sentences with no filler. The first sentence front-loads the core operation and details what is parsed; the second gives routing guidance and a behavioral promise. Every clause earns its place, and the structure is easy to scan.

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?

There is no output schema, so the description shoulders the burden of explaining return content, and it does list the key parsed sections. It also prepares the agent for miss behavior. Minor gaps remain: the exact return shape is not described, and llms_search is not referenced as an alternative, but overall the description is sufficient for correct invocation in most scenarios.

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 parameters (site, refresh, task_context) are already well documented in the schema. The description adds no parameter-level semantics beyond what the schema states, which matches the baseline of 3 for high schema coverage.

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 leads with a specific verb and resource: 'Find and parse the llms.txt that covers a site or page URL', then enumerates exactly what gets parsed (title, summary, H2 sections, Optional section, llms-full.txt probe). It also explicitly names the sibling it is differentiated from ('Use first, before llms_page'), so an agent can tell them apart.

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 gives a clear when-to-use rule: 'Use first, before llms_page, whenever the user needs a product or library's own docs'. It also provides diagnostic context ('every rung tried is returned so a miss is diagnosable') that helps the agent decide whether to call a fallback. This is explicit, actionable guidance.

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