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Get Help Doc

get-help-doc
Read-only

Read an AIdata help doc, or one section of it, as Markdown. Get slugs and section headings from list-help-docs. Pass section whenever the question concerns one part of a long doc (for example one connection type in connecting-data-sources). Base your answer on the returned text, name menus and buttons exactly as the doc does, and give the user the source link.

Input Schema

NameRequiredDescriptionDefault
slugYesDoc slug from list-help-docs, e.g. "connecting-data-sources"
sectionNoOptional section heading from list-help-docs, e.g. "Google Search Console". Omit to read the whole doc.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

The readOnlyHint=true annotation already establishes the safety profile, and 'Read ... as Markdown' is fully consistent with it. The description adds useful context beyond the annotation: the output is Markdown text and should be used verbatim as the basis for an answer. No auth or rate-limit detail, but none is expected for a read-only doc fetch.

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?

Three front-loaded sentences, each carrying a distinct load: what it does, where to get inputs, when to use `section`, and how to apply the output. No padding or repetition of schema/annotation content.

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?

With readOnlyHint covering safety, 100% schema coverage, and no output schema, the description fills the remaining gap by disclosing the Markdown return format and answer-construction guidance. An agent has everything needed to select and invoke it correctly.

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

Parameters4/5

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

Schema coverage is 100%, so both slug and section are already documented, setting a baseline of 3. The description adds genuine meaning on top by specifying when to pass `section` (long docs, one connection type) rather than merely repeating the schema's 'Optional section heading'.

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?

States a specific verb (Read) and resource (an AIdata help doc or one section of it) plus the return format (Markdown). It is clearly separable from the sibling list-help-docs, which supplies slugs and headings rather than content.

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 routes the agent to list-help-docs for slugs and section headings, and gives a concrete when-to-use rule: pass `section` when the question concerns one part of a long doc, with a worked example. It also states how to use the result (ground answers in the text, name menus/buttons verbatim, cite the source link).

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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