get_district_banking_profileBanking landscape for a congressional district: FDIC-insured institutions, total deposits/assets, recent bank failures, and representative's Banking/Financial Services committee membership.
| Name | Required | Description | Default |
|---|---|---|---|
| stateCode | Yes | Two-letter state code (e.g., GA) | |
| districtNumber | Yes | District number (0 for at-large) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true, establishing safety and potential external data sourcing. The description adds value by detailing the specific data categories (institutions, deposits, failures, committee membership) and implies no side effects, aligning with annotations. No contradictions.
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 a single, well-structured sentence that front-loads the primary purpose ('Banking landscape for a congressional district') and then lists components. No redundant or unnecessary wording.
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?
Without an output schema, the description adequately outlines the tool's return content: FDIC institutions, deposits/assets, failures, and committee membership. It covers the key areas a user would expect from a district banking profile. Minor gap: no mention of data format or pagination, but acceptable for a profile tool.
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 stateCode and districtNumber having clear descriptions. The description adds no new information about parameters beyond what the schema provides; the phrase 'for a congressional district' already echoes the schema. Baseline 3 is appropriate.
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 explicitly states the tool's function: 'Banking landscape for a congressional district' and lists specific data elements (FDIC-insured institutions, total deposits/assets, recent bank failures, committee membership). This clearly distinguishes it from sibling tools like get_district_consumer_complaints or get_district_disaster_history.
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 does not provide guidance on when to use this tool versus alternatives. For example, sibling tools like search_fdic_institutions might also provide banking data but are not mentioned. No when-not-to-use or context for selection is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.