update_document

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

With no annotations provided, the description carries the full burden and does so effectively. It discloses that content replaces the whole body, that dropping attachment:// refs removes images, that each update snapshots a new version and re-indexes for AI search, and it states the return value (updated id and state). This surfaces important non-obvious behaviors and side effects.

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 about 100 words, which is justified given the tool's complexity (content replacement, attachment refs, re-indexing). It is front-loaded with the core purpose and then addresses critical caveats. Every sentence adds value, though it could be slightly tightened without losing meaning.

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?

Given 5 parameters, no output schema, and no annotations, the description is remarkably complete. It covers partial update behavior, content replacement risks, attachment handling, side effects (versioning, re-indexing), and the return shape. It also references sibling tools (read_document, create_attachment) appropriately, providing the necessary context for safe invocation.

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?

The input schema has 100% field-level descriptions and already covers omit-to-keep semantics, content replacement, and attachment refs. The tool description reinforces these but adds little beyond the schema. It offers a global 'Any field you omit is left unchanged' statement, but that is already individually expressed in each parameter. Baseline 3 is appropriate because the schema does the heavy lifting.

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 opens with 'Edit an existing Meet Rupert document,' which is a specific verb+resource ('edit' + 'existing document') that clearly distinguishes it from creation (create_document) and other siblings like read_document or ask_ai. It also conveys the update scope by emphasizing partial edits.

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 gives explicit usage guidance: 'pass only what you want to change,' and calls out prerequisites/alternatives such as 'read_document first if you're making a partial edit' and 'Add new images via create_attachment, never by pasting image data.' It also clarifies that re-indexing occurs, affecting AI search, which helps decide when to use the tool.

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