fdic_failures

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, providing a strong safety profile. The description adds context about scope (all failures since 1934) and available filters, but doesn't disclose additional behavioral traits like pagination behavior, result size implications, or output format. It adds some value beyond annotations by clarifying the data scope, but not deep behavioral detail. No contradiction with annotations.

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?

Two sentences with zero waste. The purpose is front-loaded, followed by included fields and then filter examples. No redundancy or fluff. Every sentence earns its place, making it highly efficient.

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 5 optional parameters and no output schema, the description covers the core purpose and filtering, but omits guidance on pagination (limit/offset) and sorting (sort_by/sort_order). While these are documented in the schema, the description doesn't indicate scenarios where they're needed (e.g., large result sets). Given the annotations cover safety and the schema documents params, this is adequate but not complete—an agent might not know pagination is relevant for a dataset spanning since 1934.

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 descriptions for all five parameters. The description adds a concrete example for the 'filters' parameter: PSTALP:"GA" and a date range format, which clarifies the Lucene-style syntax beyond the schema's generic description. It also mentions the ability to combine filters, which isn't in the schema. This adds meaningful value for the most complex parameter, so above baseline 3.

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's purpose: 'Get FDIC-insured bank failures' with a scope of 'all failures since 1934'. It lists the included fields (failure date, cost, resolution type, acquiring institution) and filter options. While it doesn't explicitly differentiate from sibling tools like fdic_financials or fdic_search_institutions, the focus on 'failures' is specific enough to distinguish its intent. It's clear but not as sharp as explicitly naming a sibling alternative.

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 provides no explicit guidance on when to use this tool versus alternatives. It mentions filtering syntax (PSTALP:"GA", year range) but doesn't state conditions for choosing this tool over other FDIC datasets. The description implies usage through examples but lacks a clear 'use this when...' or 'for other data, use X' statement. No exclusions or alternatives are mentioned.

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