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Legiscan

by io.github.pipeworx-io
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List Sessions

list_sessions
Read-onlyIdempotent

List the legislative sessions for a US state (regular and special), with start/end years and session IDs. Useful to scope which session to track bills in. Example: list_sessions({ state: "NY" })

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "state": "NY"
    },
    "name": "list_sessions"
  }
}

Input Schema

NameRequiredDescriptionDefault
stateYes2-letter state abbreviation, e.g. "NY", "FL", "CA".
_apiKeyNoOptional — your own LegiScan API key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "state": "NY"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds context about output (start/end years, session IDs) and provides an example. This supplements the annotations without contradicting them.

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 plus an example, with no unnecessary words. It efficiently conveys purpose, usage context, and a concrete example. Every part 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?

The tool has low complexity with one required parameter and no output schema. The description covers what is returned (start/end years, session IDs). It lacks details like sorting or data limits, but for this simple list tool it is sufficient.

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 coverage is 100%, with both parameters (state, _apiKey) described in the schema. The description adds little beyond the schema, only showing an example with state. Baseline score of 3 is appropriate.

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 clearly states the tool lists legislative sessions for a US state, including regular and special, with start/end years and session IDs. It uses a specific verb ('List') and resource ('legislative sessions'), and distinguishes itself from sibling tools that handle bills 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.

Usage Guidelines4/5

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

The description suggests using this tool to 'scope which session to track bills in', providing clear context. It does not explicitly state when not to use or mention alternatives, but the implied use case is adequate.

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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