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Glama

Representative lookup by address

lookup_representatives
Read-only

Find federal legislators by full street address (most accurate) or by state. A full address resolves the exact congressional district via Census Geocoder. Returns bioguideId, name, party, state, district, chamber.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNo5-digit ZIP code — improves geocoding accuracy
cityYesCity name
stateYesTwo-letter state code (e.g., MI)
streetYesStreet address (e.g., "123 Main St") — required for district-level lookup

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description's behavioral disclosure is additive. It mentions the use of Census Geocoder for district resolution, which is useful context, but lacks details on error handling or rate limits.

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?

Two concise sentences that front-load the purpose and efficiently cover key information without redundancy. Every sentence earns its place.

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?

Given the moderate complexity (4 params, no output schema), the description adequately explains the geocoding process and return fields. However, it omits details on handling invalid addresses or partial lookups, but overall is complete for common use cases.

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 the schema already documents all parameters. The description adds no new parameter meaning beyond what is in the schema, maintaining the baseline of 3.

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

Purpose4/5

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

The description clearly states the tool finds federal legislators by full street address or state, and specifies the return fields. It distinguishes between accuracy levels but does not explicitly differentiate from sibling tools like get_representative_profile or list_state_delegation.

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

Usage Guidelines3/5

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

The description implies usage for address-based lookups and notes that a full address is most accurate, but provides no explicit guidance on when not to use it or alternatives. Agents may benefit from knowing when to prefer this over get_representative_profile.

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

A3.9/5.0
Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count3/5

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.

Completeness5/5

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.