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

Annotations indicate a safe, read-only, idempotent operation. The description adds substantial behavioral context beyond annotations, including the batch result shape `{ results, errors }` and a critical warning about provider incidents affecting data reliability, with explicit instruction not to present those values as real. This is high-value transparency.

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 but information-dense, with each sentence serving a purpose: what it returns, how to call it, the response shape, and a critical reliability caveat. No filler or redundancy, and it is well-structured for quick parsing.

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 the tool's batch complexity and the potential incident warnings, the description is thorough. It covers the return structure, parameter constraints, and a quality caveat that would be otherwise absent with no output schema. It provides sufficient context for an agent to use the tool correctly and interpret results safely.

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?

The schema only defines account_ids as an array of strings. The description enriches this by specifying the accepted range (1–50), the array requirement, and that it corresponds to account IDs per the endpoint, plus the batch response behavior. This fully compensates for the 0% schema description coverage.

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 uses a specific verb 'Returns' with a clear resource ('full account objects') and scope ('per id'), distinguishing it from list endpoints by emphasizing the extended creditData and the GET /accounts/:id endpoint. This effectively differentiates it from siblings like openfinance_list_accounts.

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 clearly explains how to use the tool ('Pass `account_ids` as an array (1–50)') and its batch behavior, giving a strong sense of when it applies. It does not explicitly name alternatives or exclusion criteria, but the 'per id' scope implies a contrast with list tools, making the context clear enough for an agent.

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