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Get a product’s full agent reference

get_llms_full
Read-only

Return a link to the complete, source-linked agent reference (llms-full.txt) for a product — its entire prose, API surface, and examples in one document. This file is large, so it is returned as a resource link and canonical URL rather than inlined; use search_docs/get_doc for targeted lookups and this when you want the whole corpus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productYesProduct id from list_products.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true. The description adds meaningful behavioral context: the file is large, so it is returned as a resource link and canonical URL rather than inlined. This goes beyond the annotation without contradicting it.

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: first states purpose, second adds behavioral detail and usage guidance. Every sentence earns its place, with no redundancy or filler.

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?

For a simple one-parameter read-only tool with rich annotations, the description fully covers return behavior (link/URL rather than inline), usage context, and alternatives. No output schema is present, but the description explains the return form sufficiently.

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% with a single parameter described as 'Product id from list_products.' The description adds no additional parameter semantics, but the schema already fully covers the only parameter, so 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 ('Return a link') and names a clear resource ('llms-full.txt' complete agent reference). It distinguishes itself from siblings by contrasting with targeted lookups via search_docs/get_doc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

Explicitly states when to use this tool versus alternatives: 'use search_docs/get_doc for targeted lookups and this when you want the whole corpus.' This is direct, unambiguous guidance naming both alternatives and exclusion conditions.

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

A4.4/5.0
Disambiguation4/5

Each tool has a clearly distinct role: list_products discovers products, search_docs finds pages, get_doc fetches a single page, and get_llms_full returns the whole corpus. There is minor potential for confusion between get_doc and get_llms_full about which to use, but the descriptions explicitly address this.

Naming Consistency4/5

The verb_noun pattern is consistent across all tools: list_products, search_docs, get_doc, get_llms_full. The only slight deviation is the cryptic 'get_llms_full' name, which is not immediately clear, but the pattern itself is consistent.

Tool Count5/5

Four tools is a well-scoped count for a documentation search/retrieval server. Each tool serves a necessary function in the discovery and retrieval workflow, and none feel redundant.

Completeness5/5

The surface covers the full discovery-to-retrieval flow: discovering products, searching all docs, fetching a specific page, and retrieving the entire corpus. There are no obvious gaps for documentation browsing needs.

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