Skip to main content
Glama

UK Business Tools - Ledgerhall

Search Parliamentary Divisions

law_votes_search_divisions
Read-onlyIdempotent

USE THIS TOOL WHEN searching Commons or Lords formal votes by topic, date, or member.

Returns division summaries (title, date, vote counts, pass/fail). AFTER calling, pass division_id + house into votes_get_division for the full member-by-member voter lists.

Authoritative source for UK parliamentary vote records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
houseNoWhich house to search.Commons
limitNoMaximum divisions to return. Default 25 (Commons API max-per-page).
queryNoSearch term for division titles, e.g. 'Rwanda' or 'Online Safety Bill'. Omit to browse recent divisions.
offsetNoNumber of divisions to skip before this page. Default 0. Re-call with offset=offset+returned while has_more is true.
to_dateNoEnd date (YYYY-MM-DD).
from_dateNoStart date (YYYY-MM-DD).
member_idNoFilter to divisions where this member voted. Get the member ID from parliament_find_member.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
houseYesCommons or Lords
limitNoPage size requested
queryNoThe search term, if any (None = browse recent)
totalYesNumber of divisions returned in this call
offsetNoSkip applied to this page
has_moreNoTrue if a full page was returned (more may exist)
divisionsNoMatching divisions. Use the integer `id` field with votes_get_division to fetch the full voter list.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds value by disclosing the scope of results (summaries only, not full voter lists) and the authoritative nature of the source ('Authoritative source for UK parliamentary vote records'). This helps the agent set expectations and avoid assuming full detail is present. The description does not contradict any annotations.

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 only three sentences, each with a distinct job: directive, output summary, and follow-up instruction. It front-loads the trigger condition with an all-caps 'USE THIS TOOL WHEN' and wastes no words. The structure is ideal for an agent scanning quickly.

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?

Given the rich schema, annotations, and output schema, the description covers the essential extra context: what the tool returns, the workflow to get full details, and the authoritative status. The optional browse behavior (omitting query) is already in the schema. No critical gaps remain.

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?

The input schema has 100% description coverage, with each parameter explained meaningfully (e.g., limit mentions 'Commons API max-per-page', offset explains pagination with 'has_more', member_id directs to parliament_find_member). The tool description itself only restates the search dimensions (topic, date, member) which are already evident from the schema. Per the baseline for high schema coverage, this is a 3.

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 a specific verb-resource combination: 'searching Commons or Lords formal votes by topic, date, or member.' It clearly distinguishes itself from the sibling tool votes_get_division by explaining that it returns division summaries while the full voter lists require a subsequent call to that tool.

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 opens with 'USE THIS TOOL WHEN searching Commons or Lords formal votes by topic, date, or member,' giving explicit conditions. It also tells the agent exactly what to do next: 'AFTER calling, pass division_id + house into votes_get_division for the full member-by-member voter lists,' effectively setting boundaries and directing to an alternative. No exclusions are needed beyond this.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Tools are well-grouped by domain prefixes (dd_, gov_, law_, prop_) with clear descriptions that differentiate them. However, there is minor overlap, e.g., dd_search could be used instead of individual searches, and dd_fetch versus dedicated profile tools might cause confusion.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with domain-specific prefixes (dd_, gov_, law_, prop_). Names are descriptive and predictable, e.g., dd_charity_search, gov_govuk_search, law_bills_search_bills.

Tool Count4/5

70 tools is high but justified by the broad scope covering due diligence, government, legal, and property domains. Each domain has a reasonable number of tools (about 15-20 each). The count is on the upper end but still manageable.

Completeness5/5

The tool set is comprehensive across all domains: full CRUD for companies and charities, detailed legal research (cases, legislation, parliament, citations), property data (EPC, planning, price paid, rentals), and government information. No obvious gaps for the intended use cases.

Resources