get_authorizations

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

No annotations are provided, so the description carries full responsibility. It discloses the DiVA API limit of 10,000 records per query, which is a critical behavioral trait. It also implies read-only behavior (get). However, it does not describe the response format or potential error states, but the limit disclosure is substantial.

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 two sentences long, each serving a distinct purpose: the first explains the tool's functionality and aggregation levels, the second warns about the API limit. No wasted words, and the key information is front-loaded. Ideal conciseness.

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 no output schema and complex input parameters, the description covers the core functionality, aggregation options, and a crucial performance limitation. It could mention default time ranges or prerequisite permissions, but for a data retrieval tool, the provided information is mostly sufficient. The lack of output schema details is acceptable since the tool is a standard get query.

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. The description adds value by providing an example of filter syntax (e.g., {'transaction_timestamp': '>=2023-10-20'}) and explicitly warns against including query parameters like 'count' or 'sort_by' in the filters. This extra guidance improves parameter understanding beyond the 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 clearly states the tool retrieves authorization transaction data with specific elements (amounts, counts, users, cards, merchants) and supports multiple aggregation levels. This verb+resource clarity distinguishes it from sibling tools like get_cards or get_chargebacks_detail.

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 mentions the API limit of 10,000 records and suggests using narrower date ranges or filters for larger datasets, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., when to use get_authorizations vs. get_declines or other transaction tools). Context is given for handling pagination limits, but comparative usage is missing.

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