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

The description adds workflow behavior beyond the annotations: the suggestion is a proposal for a human to accept or reject, it returns identifiers for downstream tools, and internal routing IDs are optional/resolvable from natural names. The annotations already communicate non-read-only and non-idempotent characteristics, so the description's added workflow context is valuable. No contradiction with annotations.

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?

Three tight sentences with no filler. The main action is front-loaded, followed by parameter routing guidance and then the return-value tie-in. Every sentence adds useful information for selecting or invoking the 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?

Given the complex 9-parameter schema and the presence of an output schema, the description covers the essential selection and invocation context: what the tool does, how to reference workspaces/documents naturally, and how the returned IDs connect to accept_suggestion and reject_suggestion. It could add explicit sibling exclusions or anchor-selection tips, but no major ambiguity remains.

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 description usefully explains that natural workspace names and document titles are accepted and that internal routing identifiers are optional, which helps with several parameters. However, it does not explain the two anchor forms (quote-based vs range-based), the occurrence/context fields, or how to choose between them, so the low schema description coverage is only partially compensated.

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 a specific verb and resource: 'Add an anchored replacement suggestion for a human to accept or reject.' The 'anchored' and 'replacement' qualifiers clearly distinguish it from add_comment, and the human accept/reject framing distinguishes it from direct document editing tools.

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 clearly situates this tool in a review workflow by stating it returns suggestionId and targetId 'for accept_suggestion or reject_suggestion.' It also gives practical guidance about using natural workspace names and document titles instead of internal IDs. It does not explicitly enumerate when-not cases like add_comment, but the context is clear and not misleading.

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