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adathouse
by adathouse

Run a raw GraphQL query

graphql_query

Execute arbitrary read-only GraphQL queries against the legislative API to answer complex questions like cross-referencing committee activities with bill cosponsors.

Instructions

Execute an arbitrary read-only GraphQL query against the legislative API. Use this for complex questions the specialised tools do not cover (e.g. cross-referencing committee activities with bill cosponsors). Read the 'cdg://schema' resource for the full schema. Mutations are rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA GraphQL query document. Must be a query (no mutations).
variablesNoOptional variables object for the query.
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly states that the tool is read-only and that mutations are rejected. This is key behavioral information. However, it does not mention authentication, rate limits, or error handling, which would be helpful.

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-loaded with the core purpose. It includes a usage example and a resource reference. Every sentence adds value without redundancy.

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

Completeness3/5

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

Given the complexity of a raw GraphQL tool, the description lacks information about the return format or response structure (no output schema exists). It does mention reading the input schema but not the output. The description is adequate but incomplete for a tool that returns arbitrary 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 the input schema already documents both parameters (query and variables) adequately. The tool description does not add significant meaning beyond confirming that query must not be a mutation. It does not elaborate on the variables parameter structure.

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 uses the specific verb 'Execute' and identifies the resource as 'read-only GraphQL query against the legislative API'. It clearly distinguishes itself from sibling tools by stating 'Use this for complex questions the specialised tools do not cover', making its purpose and scope unambiguous.

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 explicitly says when to use (complex questions not covered by specialized tools) and provides an example. It does not explicitly state when not to use, but the context implies that specialized tools should be preferred. The reference to reading the schema resource provides further guidance.

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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