va-lis-mcp

get_session_statistics

LIS's own bill counts for a session, by chamber of origin and legislation type.

Instructions

LIS's own bill counts for a session, by chamber of origin and legislation type.

One row per chamber and type (B bill, J joint resolution, R resolution); a type with no bills has no row. total is introduced plus continued_from_last_session, and passed counts chaptered plus vetoed bills. LIS computes these counts itself and they do not always agree with the bill list: a total can miss by a bill, the outcome columns add up differently in each session, passed_house and passed_senate are not a funnel, and continued_to_next_session overcounts (pending matches the next session). Count from list_bills when a number has to be exact.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_code": "<session_code>"
    },
    "name": "get_session_statistics"
  }
}

Input Schema

Name	Required	Description	Default
`session_code`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.0Oct 13, 2026

TDQS

A4.4/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and delivers rich behavioral context: row granularity (one row per chamber and type), an edge case (a type with no bills has no row), formula definitions (total = introduced + continued_from_last_session; passed = chaptered + vetoed), and multiple data-reliability caveats about the counts not matching the bill list.

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

Conciseness4/5

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

It is front-loaded with the tool's purpose, then row structure, then caveats, and each clause earns its place. The caveat list is dense but all of it is actionable for an agent deciding whether to trust the numbers.

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?

An output schema exists, so return values need not be explained, and the description adequately covers behavior, edge cases, and reliability warnings. The only real gap is the unexplained `session_code` parameter, which keeps it from being complete.

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

Parameters2/5

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

Schema description coverage is 0% for the single `session_code` parameter, and the description never explains its meaning or format (it is an integer, not a human-readable session). The tool operates "for a session," but the parameter itself is left undocumented, so the description fails to compensate for the coverage gap.

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 states a specific resource and scope: "LIS's own bill counts for a session, by chamber of origin and legislation type." It distinguishes itself from the sibling `list_bills` by framing itself as the aggregate count source rather than the bill list.

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

Usage Guidelines5/5

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

It gives explicit when-not guidance (counts "do not always agree with the bill list") and names the alternative with the condition that selects it: "Count from list_bills when a number has to be exact." This is exactly the routing information an agent needs to choose between the two tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.