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Read a documentation page

get_doc
Read-only

Fetch a single documentation page as Markdown, given a product id and a page slug (both come from list_products / search_docs results, or a doc URL like /liteship/overview). Returns the title, description, a heading outline, and the full Markdown body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesPage slug, e.g. "overview" or "factory" (from search_docs results or the last path segment of a doc URL).
productYesProduct id from list_products (e.g. "liteship", "batpak").

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, but the description adds valuable return details: title, description, heading outline, and full Markdown body, as well as output format. It also confirms 'single page' scope, which is not in the annotations.

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?

One dense sentence conveys the action, inputs, output, and parameter provenance without filler. It is front-loaded with the core purpose and every clause earns its place.

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 read-only tool with two well-documented parameters and no output schema, the description covers inputs, output, and format. There are no significant gaps in the context needed 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 coverage is 100% and both parameter descriptions already include examples and source references. The description adds no new semantic detail beyond what the schema provides, so it stays at baseline.

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?

Description uses specific verb 'Fetch' and identifies the resource as 'a single documentation page as Markdown', with clear inputs (product id and slug). It distinguishes itself from siblings: list_products lists products, search_docs searches, while get_doc pulls a specific page.

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 says parameters 'come from list_products / search_docs results, or a doc URL', providing clear context on how to obtain inputs. However, it does not explicitly state when to prefer get_doc over search_docs or list_products, nor does it describe exclusions.

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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