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Search Legislators

search_legislators
Read-onlyIdempotent

Find state legislators. Filter by jurisdiction, name, chamber (upper/lower), party, or district. Returns name, current/prior roles, party, contact details, OpenStates IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName fragment
pageNo1-based page
partyNoParty name (e.g., "Democratic", "Republican")
districtNoDistrict identifier
per_pageNo1-50 (default 20)
jurisdictionNo2-letter state code or name
org_classificationNoupper | lower | legislature

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYesCurrent page number
totalYesTotal matching legislators
returnedYesNumber of legislators in response
legislatorsYes
total_pagesYesTotal number of pages

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint=false, so the description is not the sole bearer of safety information. The description adds value by disclosing that results include current/prior roles and contact details, giving the agent a sense of the data scope and temporal coverage. No contradictory behavior is mentioned, and it correctly aligns with the read-only, idempotent nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loads the core purpose, and packs filter and return-field information efficiently. No filler or redundant content exists, making it easy to scan and process.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 optional parameters, an output schema, and strong annotations (read-only, idempotent, open-world), the description covers the essential purpose, filtering capabilities, and result content. Pagination semantics are implied by the schema's page/per_page parameters, and the output schema handles return details. Minor omissions like implicit AND-filter behavior are not critical given the available structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are already well-documented. The description restates the filter keys (jurisdiction, name, chamber, party, district) but adds little beyond what the schema provides, except clarifying the "chamber" term corresponds to org_classification. This meets the baseline for high schema coverage without substantially enriching parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with "Find state legislators," a specific verb+resource combination that clearly identifies the tool's function. It further differentiates from siblings like get_legislator (single-record fetch) by listing filter dimensions (jurisdiction, name, chamber, party, district) and the returned fields (name, roles, party, contact details, IDs), making the search scope explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys clear search-and-filter context, and the mention of filter fields implies it is for exploratory lookups rather than point lookups. It does not explicitly name alternatives or when-not-to-use scenarios, but its clarity and the presence of sibling tools like get_legislator provide enough implicit guidance for an agent to select this tool appropriately.

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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TDQS

B3.1/5.0
Disambiguation1/5

The tool set includes multiple pairs of nearly identical tools (e.g., ask_pipeworx and ask_pipeworx_grounded, bet_research and polymarket_arbitrage) that overlap heavily in purpose. Many tools also combine unrelated functions, making it difficult for an agent to select the right one without confusion.

Naming Consistency1/5

Tool names follow no discernible pattern: snake_case (ai_visibility_check), verb_noun (ask_pipeworx, get_bill), and even lengthy descriptive names (scan_competitor_ai_presence) are mixed. The naming style is chaotic and inconsistent across the set.

Tool Count2/5

With 30 tools, the count is excessive for a server supposedly focused on OpenStates (state legislatures). Only a few tools (search_bills, get_bill, etc.) relate to the server's name, while the rest are tangentially related to data lookups, betting, or AI visibility, making the set bloated.

Completeness1/5

The server's core domain (state legislative data) is severely underserved: only about 5 tools cover bills and legislators, lacking basic CRUD operations like create, update, or delete. Many obvious operations (e.g., searching bills by subject, tracking votes) are missing, while unrelated tools dominate.