docs_batch_update

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

With no annotations provided, the description carries the full disclosure burden. It adds valuable behavioral context: the operation is a single round-trip, atomic, and consumes raw API payloads. However, it does not disclose failure semantics, request ordering, batch size limits, or the mutation's irrevocability — meaningful gaps for a raw batch API tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence with a front-loaded verb and resource. The em-dash clause adds the key usage context (combining edits atomically) without padding. Every word earns its place; it is efficient and appropriately sized for a two-parameter tool.

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

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

The tool is complex — it accepts arbitrary raw request objects — yet no annotations are provided. The description covers the core purpose, atomicity, and round-trip benefit, and an output schema exists so return values are covered. However, it lacks operational details an agent would need for safe batch use, such as request ordering, per-batch request limits, and behavior when one sub-request fails.

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

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

Schema description coverage is 0%, so the description must compensate. It clarifies that 'requests' is a list of raw Docs API batchUpdate payloads and gives examples of edit types (text, styling, tables, images), which adds meaning beyond the bare schema. However, it does not explain the structure of individual request items or the document_id parameter beyond what the parameter name implies, leaving the agent to consult external API docs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource structure: 'Apply a list of raw Docs API batchUpdate requests in one round-trip.' It clearly distinguishes itself from the many sibling docs_* single-operation tools (docs_insert_text, docs_format_text, etc.) by positioning itself as the raw batch mechanism. It also conveys the scope ('many edits: text, styling, tables, images') and the atomic-call benefit.

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

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

The description explicitly frames when to use this tool: when you want to 'combine many edits... into a single atomic call instead of many tool calls.' This gives clear context contrasting it with the individual docs_* editing tools. However, it does not name specific alternatives or state when not to use it (e.g., for a single simple edit), so it falls just short of explicit exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.