AI-Process Bank Cheque

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

With no annotations, the description discloses the async polling behavior (202 + Location poll), the output file (process_bank_cheque.json), and the specific request body casing requirements. It does not cover error handling or authentication, but provides substantial behavioral context beyond mere inputs.

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 front-loaded with the core purpose and then provides dense technical details. It is logically structured but slightly long; all sentences contribute value, with no wasted words.

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 description covers the main operational aspects: async flow, file output, parameter formats, and casing. Given no output schema or annotations, it is quite complete, but lacks explicit mention of output_dir's purpose and the JSON response structure beyond 'full API JSON'.

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?

Three of four parameters are explained: pdf_file_path (Base64, accepted formats), doc_name (logical name, optional with default), and custom_field_keys (non-empty list, omitted if unused). However, output_dir is not described, leaving a gap in parameter understanding.

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 'extract structured data from a bank cheque', using a specific verb and resource. It clearly distinguishes from sibling process_* tools by targeting bank cheques specifically and also references the API endpoint.

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 implies use for bank cheque extraction and warns against confusing its parameter casing with AI-Invoice Parser, but it does not explicitly state when to use this tool vs alternatives or list exclusion criteria. Sibling tools for other document types are not mentioned.

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