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

Annotations already cover non-destructive and idempotent behavior, so the bar is lower. The description adds meaningful partial-update semantics with 'Only provided fields are updated', which tells the agent that omitted fields remain unchanged.

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?

Two concise sentences both earn their place: the first states the action, resource, and fields, and the second states the intended use case. Information is front-loaded with no filler.

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 has a simple flat schema, an output schema, and annotations covering idempotency and destructive risk. The description sufficiently covers scope, behavior, and use case, leaving no critical gap for an agent to invoke it correctly.

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 high (86%), so the schema already explains each parameter. The description adds value by grouping these as analytics fields and stating partial-update behavior, but it does not provide new per-parameter meaning.

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 and resource ('Update analytics fields on a chat request') and lists all possible fields. It also distinguishes itself from sibling update_* tools by naming the chat-request resource and its analytics purpose.

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 phrase 'Use this to annotate or reclassify chat interactions after the fact' provides clear intended context. It does not explicitly name alternatives or exclusions, but no direct sibling alternative for this update operation exists.

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