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

Although annotations mark it readOnly and idempotent, the description goes further, disclosing it makes one outbound HTTP request, stores nothing, requires no authentication, and shares a rate limit. This adds value beyond annotations and gives the agent a clear safety and side-effect profile.

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 a single paragraph with multiple sentences, but all sentences carry important information. It is front-loaded with the main action and result, and the rate limit follows. Slightly verbose but efficient for the information conveyed.

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?

For a single-parameter tool with no output schema, the description covers the input, behavior, edge cases (missing file), and limitations. It lacks nothing an agent needs to call it correctly, considering the annotations cover safety.

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% and the description does not elaborate on the domain parameter beyond what the schema states. The description emphasizes bare domain format implicitly through the example, but the schema already covers that. 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?

The description clearly states the tool fetches llms.txt from a domain and grades it with seven deterministic checks, returning a score and pass/miss results. It distinctly differentiates from siblings by specifying the exact file and grading function, which is not shared by any sibling.

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?

Explicitly says when to use: when a user asks if a site is AI-readable or wants llms.txt reviewed. It also implies when not to use by focusing on llms.txt, and mentions sharing a rate limit with cold_read, which helps the agent choose among tools.

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