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UK Legal Research

by io.github.paulieb89

Get Member Debates

parliament_member_debates
Read-onlyIdempotent

USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim (text-body search).

CALL parliament_find_member(name) FIRST to obtain the integer member_id.

This is a name-based text-body search — it matches contributions whose TEXT contains the topic phrase. A member who spoke in a debate but didn't use your phrase verbatim is filtered out. For verbatim retrieval of every contribution by a member in a known debate (regardless of vocabulary), use parliament_get_debate_contributions(debate_ext_id, member_id=...) instead.

Each contribution's text field is capped at 3000 characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum contributions to return. Default 20.
topicNoOptional phrase to find in THIS member's contribution text bodies. Hansard searches the words the member actually said, NOT the topic or title of the debate. Pass tokens this member would have spoken — distinctive arguments ('disproportionate sanction'), statutory references ('section 21'), or motion numbers ('Motion C1') — not the bill's name (members rarely say e.g. 'Renters\' Rights Bill' verbatim in their speeches). If you want 'every contribution this member made in a specific debate' regardless of words used, find the debate_ext_id then use parliament_get_debate_contributions(debate_ext_id, member_id=...).
offsetNoNumber of contributions to skip before this page. Default 0. Re-call with offset=offset+returned while has_more is true.
member_idYesParliament Members API integer ID. Obtain from parliament_find_member.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size requested
topicNoTopic phrase filter applied, if any
totalYesNumber of contributions returned in this call
offsetNoSkip applied to this page
has_moreNoTrue if a full page was returned (more may exist)
member_idYesParliament Members API member ID
contributionsNoHansard contributions for the member. Each `text` field is capped at 3000 characters.

TDQS

A5/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive behavior, but the description adds valuable context: text-body search semantics, filtering of members who didn't use the phrase, the 3000-character cap on contribution text, and the prerequisite of obtaining member_id. This goes beyond the annotations to explain real behavioral constraints.

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 front-loaded with a clear usage directive, followed by a prerequisite, then semantic clarification and an alternative. Each sentence serves a distinct purpose; the length is justified by the tool's complexity and the need to prevent misuse.

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

Completeness5/5

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

For a read-only, well-annotated tool with a rich output schema, the description covers all necessary context: when to use, prerequisites, search semantics, limitations (3000-char cap), and the alternative for complete retrieval. No gaps are evident.

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

Parameters5/5

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

While schema coverage is 100%, the description adds significant meaning, especially for the 'topic' parameter: it clarifies that the search targets the member's actual spoken words, not debate titles, and gives examples of effective search tokens. It also explains offset pagination behavior, enriching the schema's basic parameter descriptions.

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 identifies the tool's purpose: retrieving contributions where a specific member used a specific topic phrase verbatim in a text-body search. It distinguishes from the sibling tool parliament_get_debate_contributions by clarifying this is a name-based text-body search, not a full debate retrieval.

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?

The description explicitly states when to use this tool ('USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim'), requires calling parliament_find_member first, and names the alternative tool for retrieving all contributions regardless of vocabulary. This is explicit and actionable.

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

A4.4/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose, with detailed descriptions that prevent ambiguity. Tools covering similar domains (e.g., multiple parliament search tools) are carefully differentiated by their search approach and input requirements.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (e.g., bills_get_bill, case_law_search, citations_resolve). Even generic tools adhere to this style. No mixing of conventions.

Tool Count4/5

With 35 tools, the count is on the higher side but appropriate for the wide-ranging domain of UK legal research. Each tool contributes to specific sub-domains (bills, case law, citations, committees, HMRC, legislation, parliament, votes) without unnecessary duplication.

Completeness5/5

The tool surface covers nearly all essential aspects of UK legal research: searching and retrieving bills, case law, and legislation; parsing and resolving citations; exploring committee evidence; accessing Hansard debates and member interests; and checking HMRC guidance and VAT rates. Gaps like full judgment text retrieval are mitigated by paragraph-level access and indexing.

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