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Read a Google Doc

read_doc

Read Google Docs content as markdown with inline HTML, choosing clean or tracked-suggestions mode and including headers, footers, or body segments.

Instructions

Read a Google Doc as markdown + inline HTML. mode: clean (committed text, default) · tracked (suggestions shown as /) · accepted · rejected. segment picks the content tree: body (default), header, footer, or all (body plus every header/footer, each labelled). A body read always reports which headers/footers exist and what they hold, since their content — a letterhead logo, a page number — is NOT part of the body and would otherwise be invisible.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabNoTarget a specific tab by tabId or title (from list_tabs). Defaults to the first tab.
modeNoread mode (default clean)
pageNowhich header/footer, when a doc defines more than one (default-page, first-page, even-page). Omit to use whichever exists.
accountNoGoogle account email to use. Defaults to GDOCS_DEFAULT_ACCOUNT, or the sole account.
segmentNocontent tree to read (default body)
documentIdYesGoogle Doc id
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses a non-obvious behavior: a body read always reports headers/footers and their content, even though that content is not part of the body. It also clarifies how tracked mode renders suggestions as <ins>/<del>. It doesn't explicitly state read-only, but the verb 'Read' implies 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?

Four sentences, front-loaded with the core purpose, then progressively detailed explanations of modes, segments, and the header/footer quirk. Every sentence earns its place; no filler.

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

Completeness4/5

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

The description covers the most important behavioral nuances for a read tool: output format, mode semantics, segment options, and the invisible-content quirk. The schema already documents parameters like tab, page, and account, so the description needn't repeat them. For a tool without an output schema, this is adequately complete.

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 baseline is 3. The description adds substantial meaning to mode ('clean (committed text, default) · tracked (suggestions shown as <ins>/<del>)') and segment ('body plus every header/footer, each labelled'), beyond the bare enum values. Useful context, but not every parameter is enriched.

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 opens with 'Read a Google Doc as markdown + inline HTML' – a specific verb, resource, and output format. The modes and segments clarify scope, distinguishing this from sibling mutation tools like edit_doc or overwrite_doc.

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

Usage Guidelines3/5

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

The description explains modes and segments, giving implicit guidance on when to use each, but it never names alternatives like export_doc for other formats or list_suggestions for suggestion-only queries. Usage context is implied, not explicit.

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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