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llms.txt for agents

llms_index

Read-onlyIdempotent

Find and parse the llms.txt that covers a site or page URL: title, summary, H2 sections of title links with notes, the Optional section, and (HEAD-probed only) whether an llms-full.txt exists. Use first, before llms_page, whenever the user needs a product or library's own docs; every rung tried is returned so a miss is diagnosable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite or page URL, e.g. "docs.stripe.com" or "https://hono.dev/docs/". The most specific covering llms.txt wins.
refreshNoBypass the 24 h cache and fetch again.
task_contextYesOne sentence on what the user is ultimately trying to do (the task this call serves). Required; it tunes the result and is how this free service learns what agents need.

TDQS

A4.5/5.0
Behavior5/5

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

With readOnly, openWorld, and idempotent annotations already covering safety and side effects, the description adds valuable behavioral context: the HEAD-probed nature of the llms-full.txt check, the fact that every attempted rung is returned, and that misses are diagnosable. This goes well beyond what annotations alone communicate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The core behavior and output contents are front-loaded, and the usage guidance follows naturally. Every clause earns its place, and the structure gives the agent the key decision information early.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description conveys what will be returned (title, summary, H2 links, Optional section, llms-full.txt indicator) and how failures behave ('every rung tried is returned so a miss is diagnosable'). Combined with the annotations and the sibling-routing guidance, an agent has enough context to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters. The description reinforces the URL-centric purpose and mentions the parsed output, but it does not add meaningful detail about the parameters themselves beyond what the schema provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Find and parse') with a clear resource ('the llms.txt that covers a site or page URL') and enumerates the exact parsed contents (title, summary, H2 sections, Optional section, llms-full.txt existence). It also differentiates from the sibling llms_page by saying 'Use first, before llms_page,' so an agent can distinguish it 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.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'Use first, before llms_page, whenever the user needs a product or library's own docs.' This provides clear routing relative to llms_page. It does not explicitly mention when llms_search would be preferable, so the guidance is strong but not fully exhaustive.

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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TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a clear and distinct role: llms_index discovers and parses the index, llms_page fetches a single documentation page, and llms_search queries previously parsed indexes. There is no meaningful overlap between them.

Naming Consistency5/5

All tool names follow the same llms_ prefix with a simple verb-like suffix: index, page, search. This creates a predictable and consistent convention.

Tool Count5/5

Three tools is well-scoped for a focused llms.txt utility server. Each tool covers a distinct necessary step in the workflow without redundancy or bloat.

Completeness4/5

The core workflow is covered: locate an index, search it, and retrieve individual pages. A minor gap is the lack of an explicit tool for directly fetching an llms-full.txt file, though llms_page may partially cover this.