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

With no annotations provided, the description carries the full disclosure burden and meets it: it reveals the two access levels ('full' vs 'preview'), the 5-sample-row limitation, the $9.99 unlock_url, the 1-3 minute latency for large statements, and the 'processing' status path. This gives an agent a realistic model of the tool's behavior beyond the schema.

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 compact and information-dense: three sentences cover input format, return contract, pricing, access-level semantics, latency, and polling behavior. Nothing is wasted, and the primary action is front-loaded in the first sentence.

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?

For a tool with no output schema and no annotations, this description is remarkably complete: it specifies accepted inputs, required encoding, response contents, access-level behavior, pricing, expected duration, and the async status path. An agent has enough context to invoke it correctly and handle the outcome.

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 100%, so the baseline is 3, but the description adds meaningful value by enumerating accepted file extensions (PDF, CSV, XLS, XLSX, OFX) and reinforcing that content is sent as base64. This supplements the filename and content_base64 parameter meanings beyond the schema's brief descriptions.

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 names a specific action (upload and run AI extraction + categorisation) on a specific resource (a bank statement file) and states its outputs (session_id, access.level). It also distinguishes itself from siblings by positioning itself as the upload/conversion entry point and explicitly telling the agent to poll get_job when status is 'processing'.

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 clear context for when to use this tool: uploading a statement in accepted formats. It names the sibling get_job as the polling follow-up when processing is incomplete, but it does not explicitly explain when to use get_transactions instead. This is clear enough for most cases but stops short of explicit when-to-use versus all alternatives.

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