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

With no annotations, the description carries the behavioral burden and does it well: it reveals asynchronous extraction, the returned information (status and memory count), and the identifier contract exception. It stops short of stating read-only behavior or error semantics, but the core behavior is transparent.

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?

Four sentences, each earning its place: purpose, parameter source, return value, usage rationale, and identifier-contract exception. The most important information is front-loaded and there is 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?

Given a single required parameter, an output schema that can carry return-value details, and sibling tools providing surrounding context, the description covers what an agent needs: what the tool does, when to use it, and how to obtain the parameter.

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 coverage is 0%, so the description must compensate, and it fully does. It tells the agent exactly where to get ingestion_id ('returned by log_exchange') and explains why no user_id or customer_id is needed, adding meaning far beyond the bare string schema.

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: 'Check whether a logged exchange has finished processing.' It clearly defines the tool's scope and differentiates it from siblings by clarifying that it takes no user_id or customer_id, since the ingestion_id already identifies the write.

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 situational guidance: use it to confirm a save completed because extraction is asynchronous, and pass the ingestion_id from log_exchange. It does not enumerate when-not-to-use alternatives, but the intended workflow is clear.

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