validate_llms_txtChecks pasted llms.txt against the format: one H1, a blockquote summary, H2 sections of - [name](url): notes. Errors and warnings with line numbers and fixes, plus the parsed links. Text in, nothing fetched. Example: text='# Site' warns it has no summary and no sections.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The llms.txt content itself, not a URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only, idempotent, and non-destructive, so the description is free to add behavioral detail. It describes the validation output ('errors and warnings with line numbers and fixes, plus the parsed links'), the exact format expectations, and that no fetching occurs. The example ('# Site' warns about missing summary and sections) further clarifies real behavior. No contradiction with annotations.
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?
Three sentences, each earning its place: the first defines scope and format, the second describes outputs and the no-fetch guarantee, and the third gives a concrete illustrative example. The key information is front-loaded and there is 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?
For a single-parameter, read-only validation tool with no output schema, the description is complete. It states what input is expected, what format is checked, what return contents to expect (errors, warnings, line numbers, fixes, parsed links), and the no-network boundary. Nothing an agent needs to correctly invoke the tool is missing.
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 parameter description already states the text is 'llms.txt content itself, not a URL,' so the baseline is 3. The description adds value by specifying the llms.txt format in detail and giving an example value ('text=# Site' warns ...), which helps the agent understand what kind of string to pass. This goes slightly beyond the schema without repeating it.
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 a specific verb ('Checks'), names the resource ('pasted llms.txt'), and immediately specifies the format being validated. The opening sentence alone differentiates it from siblings like llms_txt_from_sitemap (which fetches from a sitemap) and validate_agent_card (which validates a different artifact), so an agent can identify the tool without opening the schema.
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 phrase 'pasted llms.txt' and 'Text in, nothing fetched' clearly indicate this tool is for already-obtained text content, not URLs or fetches. This gives a clear context for when to use it, especially relative to llms_txt_from_sitemap. It does not explicitly name alternatives or exclusion cases, but the input boundary is strong enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: live host probing, catalogue explanation, llms.txt generation, agent card validation, and llms.txt validation. Even check_discovery_documents and explain_document are clearly separated as 'probe a host' versus 'look up a catalogue entry.'
Most tools follow a clear verb_noun pattern like check_discovery_documents, explain_document, and validate_agent_card. However, llms_txt_from_sitemap breaks the pattern by being a noun phrase with no verb, making it slightly inconsistent.
Five tools is well-scoped for a specialized agent discovery auditing server. Each tool earns its place and there is no obvious redundancy or bloat.
The set covers the core workflows: auditing hosts, explaining documents, and validating two key formats. Minor gaps exist, such as no generator for agent cards or validators for the other 20 probed document types, but agents can still accomplish the main purpose.