search_consumer_complaintsSearch CFPB consumer complaints by company, product, state, or date range. Returns complaint details including issue, response, and timeliness.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Max results (default 25) | |
| state | No | Two-letter state code | |
| dateTo | No | End date (YYYY-MM-DD) | |
| company | No | Company name to filter by | |
| product | No | Product type (e.g., "Credit reporting") | |
| dateFrom | No | Start date (YYYY-MM-DD) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the description adds minimal behavioral context; it only notes return fields without disclosing pagination, rate limits, or data freshness.
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 concise sentences front-load the purpose and return details, with no extraneous or redundant information.
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 key filter and return aspects, but lacks information on default behavior when no filters are provided and does not mention pagination despite the size parameter.
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 provides 100% description coverage for all 6 parameters, and the tool description merely summarizes filter types without adding new semantic meaning, meeting the baseline expectation.
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 searches CFPB consumer complaints and lists specific filter fields (company, product, state, date range) and return fields (issue, response, timeliness), distinguishing it from sibling analysis tools or other search tools.
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 usage for raw complaint search via listed filters, but does not explicitly state when to use this tool versus sibling search or analysis tools, nor does it mention alternatives or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a clear, specific purpose with detailed descriptions that differentiate them. Prefix patterns like get_district_, search_, analyze_, get_, etc., help an agent easily identify the correct tool for a task.
All tool names use a consistent verb_noun or verb_noun_noun pattern with underscores. The naming convention is uniform across the entire set, with no mixing of styles or ambiguous verbs.
With 47 tools, the count is high but justified by the broad scope of civic data analysis. While some agents might find the sheer number overwhelming, the tools are organized into clear categories (district profiles, searches, analyses) that make navigation feasible.
The toolset covers an impressively wide range of domains: legislation, representatives, districts, voting, committees, campaign finance, lobbying, federal spending, regulations, environment, energy, healthcare, housing, disaster, banking, consumer complaints, crime, vehicles, and more. There are no obvious missing operations for a civic data platform.