List the cosponsors of one bill with their party and state. Useful for mapping coalitions behind legislation. Requires Congress number, bill type, and bill number.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max cosponsors (default 250). | |
| congress | Yes | Congress number. | |
| bill_type | Yes | Bill type code: hr (House Bill), s (Senate Bill), hjres, sjres, hconres, sconres, hres, sres. | |
| bill_number | Yes | Bill number. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds useful context about return content (party and state) and the required identifiers, but does not disclose edge behaviors such as ordering, pagination, or behavior when a bill has no cosponsors.
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 concise and front-loaded with the core action and resource. The final sentence about required parameters is somewhat redundant given the schema's required array, but it does reinforce key invocation details without adding significant bloat.
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 read-only tool with no output schema, the description adequately states what the tool returns (cosponsors, party, state) and what inputs are needed. It does not describe all potential response details or error cases, but those are less critical given the annotations and schema.
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 description coverage is 100%, so all parameters are already documented. The description adds no parameter semantics beyond restating that Congress number, bill type, and bill number are required, which is already in the schema. A baseline of 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 uses a specific verb ('List') and resource ('cosponsors of one bill'), and specifies the returned fields ('party and state'). This clearly distinguishes it from sibling tools like congress_bill_actions or congress_bill_details, which focus on other aspects of legislation.
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 phrase 'Useful for mapping coalitions behind legislation' provides clear context for when to choose this tool. It does not explicitly name alternatives or state when not to use it, so it misses the top score, but the guidance is sufficient for most selection decisions.
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.
Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.
The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.
290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.
For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.