Get the auto-generated llms.txt for a cataloged company: a curated, AI-readable guide to the business.
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"domain": "<domain>"
},
"name": "get_llms_txt"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the llms.txt is 'auto-generated' and 'curated, AI-readable', which gives some behavioral context. However, it doesn't explicitly state side effects (though 'get' implies read-only), access requirements, or error behavior. No annotations exist, so the description carries the full burden and only partially fulfills it.
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, front-loaded sentence with no fluff. It efficiently conveys the tool's core function and the nature of the output.
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 the tool's simplicity (one parameter, no output schema), the description covers the core purpose but lacks usage guidelines and explicit parameter format. It also doesn't mention potential errors or prerequisites like catalog membership. It is adequate but has clear gaps in guidance.
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?
With 0% schema description coverage, the description must explain the domain parameter. It only says 'for a cataloged company', which hints at domain's role but doesn't specify format (e.g., 'example.com'), validation rules, or what happens if the domain isn't cataloged. The agent gets insufficient parameter semantics.
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 uses the specific verb 'Get' with the resource 'llms.txt' and adds context 'for a cataloged company', clearly distinguishing this from sibling tools that retrieve other data types. It is specific and unambiguous, naming a unique deliverable.
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?
No guidance is provided about when to use this tool instead of siblings like get_company_facts or get_citations. There are no use-case examples or alternative tool mentions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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