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ChrisBrooksbank

UK Parliament MCP Server

get_hansard_speakers_for_day

Find out who spoke in a specific Hansard section on a given date by providing the date, house, and section; returns the list of speakers.

Instructions

Get list of speakers for a specific sitting day section | Hansard, speakers, daily list | Use to find who spoke in a particular section of parliamentary business on a given day | Returns list of speakers for that section

    Args:
        date: Date in YYYY-MM-DD format.
        house: House: 1 or 'Commons', 2 or 'Lords'.
        section: Section name (e.g. 'Debate', 'WestHall', 'Petitions', 'GEN').

    Returns:
        List of speakers for the specified day and section.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes
houseYes
sectionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It states what is returned but says nothing about behavior on non-sitting days, missing sections, permission requirements, or result ordering. It is a mere lookup, so the risk is low, but the description adds little behavioral context.

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

Conciseness3/5

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

The core purpose is front-loaded, but the opening line and the 'Returns' clause restate the same point ('list of speakers... Returns list of speakers for that section'), and the pipe-delimited keyword block adds little. The Returns section is also redundant given an output schema exists.

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?

Parameters are fully documented, which is the main need, and an output schema is present so return values need not be spelled out. The missing piece is routing among the many Hansard siblings, which the description never addresses.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry parameter meaning and it largely does: date as YYYY-MM-DD, house as 1/'Commons' or 2/'Lords', and section with concrete examples ('Debate', 'WestHall', 'Petitions', 'GEN'). It adds real value beyond the bare typed schema, though it omits defaults and fallback behavior.

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?

States a specific verb and resource: 'Get list of speakers for a specific sitting day section.' An agent can tell it returns speaker names rather than debates. However it does not distinguish itself from close siblings like get_debate_speakers or search_hansard_members, which is a real gap in this crowded Hansard namespace.

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?

'Use to find who spoke in a particular section of parliamentary business on a given day' implies the right context, but there is no explicit when-not guidance and no named alternative (e.g. get_debate_speakers for speakers by debate). Usage is inferable but not directed.

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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