Extract IBANs From Text

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description doesn't need to repeat safety. It adds valuable details: input is processed in memory and not stored, and text with no IBAN returns empty list rather than an error. This goes beyond annotations, but could mention validation criteria or output format more explicitly.

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?

Every sentence serves a purpose: main action, use cases, output behavior, relationship to sibling, privacy. No redundant phrases, front-loaded with key verb and resource, and logically organized.

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 single-parameter tool with no output schema, the description is remarkably complete. It covers input types, edge cases (no IBAN), output structure (JSON array with validation result), privacy properties, and relationship to sibling tools. The agent has all info needed to use 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 coverage is 100% with description for 'text' parameter. The description adds semantic value beyond the schema by explaining that text can be arbitrary, IBANs may be split across spaces, and it gives examples of input types (emails, invoices). This helps the agent understand acceptable input formats.

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 clearly states the tool scans free-form text, extracts candidate IBANs, validates them, and returns results. The verb 'extract' paired with resource 'IBANs from text' is specific, and it distinguishes itself from sibling tools like 'validate_bulk_ibans' by being the first step for messy text.

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?

Explicitly states when to use: unstructured sources like emails, invoices, PDFs, chat messages. It also says when not to use (no IBAN returns empty list) and suggests using 'validate_bulk_ibans' as a follow-up if needed. Provides clear alternatives and context.

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