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llms.txt for agents

llms_page

Read-onlyIdempotent

Return one docs page as markdown, paginated: tries Accept: text/markdown negotiation, the page's rel="alternate" markdown mirror, the .md / .html.md / index.md conventions, then a bounded HTML-to-markdown conversion. Use on the URLs llms_index returns, or on any docs URL you already hold.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPage URL (http/https).
offsetNoCharacter offset to continue from (use next_offset from a truncated result).
max_charsNoCharacters of markdown to return in this call.
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?

The description thoroughly discloses the internal fallback chain (Accept negotiation, alternate markdown mirror, file conventions, final HTML-to-markdown conversion) and the bounded pagination behavior. This goes well beyond the readOnly and idempotent annotations, giving the agent a realistic expectation of how the tool behaves and what it may return.

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?

The description is a single, information-dense sentence that front-loads the core purpose and pagination behavior before the usage note. Every clause adds value, and there is no filler or repetition of schema details.

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?

The tool is moderately complex, but the description covers its purpose, input source, fallback behaviors, pagination, and the role of task_context. No output schema exists, yet the mention of 'truncated result' in the offset parameter plus the markdown return behavior is sufficient for correct invocation.

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 coverage is 100%, so the parameters are already fully documented in the input schema. The description adds helpful context about pagination and the source of URLs, but it does not add substantial new parameter-level meaning beyond what the schema already provides.

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 states a specific action ('Return one docs page as markdown') and a clear resource ('docs page'), with pagination behavior explicitly mentioned. It also distinguishes itself from siblings by referencing llms_index as the source of URLs, making its role in the tool family clear.

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 gives explicit guidance: 'Use on the URLs llms_index returns, or on any docs URL you already hold.' This clearly states when to use the tool. It does not explicitly mention llms_search as an alternative or state when not to use it, but the context is still clear enough for an agent.

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.