get_committee_infoGet detailed information about a congressional committee including members, jurisdiction, and subcommittees.
| Name | Required | Description | Default |
|---|---|---|---|
| committeeId | Yes | Committee identifier (e.g., HSIF for House Energy & Commerce) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds no additional behavioral context beyond purpose. It does not disclose any special constraints or side effects, but annotations cover reading safety.
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?
Single sentence front-loads the action and resource, includes key outputs. No wasted words.
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 simple retrieval tool with one parameter and no output schema, describing members, jurisdiction, and subcommittees is sufficient. Could mention that committeeId format is required but schema already provides example.
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 covers 100% of the single parameter with a clear description and example. Description does not enhance parameter semantics beyond listing returned fields.
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?
Specific verb 'Get' and resource 'congressional committee' clearly indicate purpose. Lists contents (members, jurisdiction, subcommittees) and distinguishes from siblings which focus on analysis or other entities.
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?
Description implies use when committee details are needed but provides no explicit usage context, prerequisites, or exclusions. With many sibling tools, lack of when-not-to-use guidance is a gap.
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.