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Glama

Legislation Uk

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, establishing safe operation. The description adds valuable context: it fans out to multiple sources, uses fallbacks, and mentions USPTO soft-failure. However, it could disclose rate limits or error handling more explicitly.

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?

The description is a single paragraph that efficiently front-loads key information with example queries, then provides details. It is slightly verbose but every sentence adds value. Could be improved with more structured formatting (e.g., bullet points for sources).

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 tool's complexity (multiple sources, fallback, soft-failure, no output schema), the description is remarkably complete. It describes the output format, constraints on USPTO, and distinguishes from sibling tools. No important gaps remain.

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 100%, so baseline is 3. The description adds significant meaning beyond schema: explains `since` format with examples, recommends typical values, and clarifies that `value` accepts tickers or CIKs. This extra detail justifies a higher score.

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's purpose as a 'change feed for a company in the last N days/weeks/months' with specific verbs and resources. It also distinguishes itself from the sibling 'entity_profile' tool by explicitly noting when the alternative should be used.

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?

Provides explicit guidance on when to use this tool versus alternatives (e.g., 'Use entity_profile instead when you want the static profile'). Also includes example queries and explains the fallback mechanism (GDELT→GNews) for when to use which data source.

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

A3.9/5.0
Disambiguation2/5

The four legislation tools are clearly distinct, but the set as a whole is confusing: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and entity_profile, compare_entities, recent_changes, validate_claim, and ask_pipeworx_grounded have overlapping research/verification purposes. The 31 non-legislation tools also create constant ambiguity about which tool to pick for a UK law question.

Naming Consistency4/5

Names are uniformly lowercase snake_case and mostly follow recognizable verb-led or prefixed patterns (get_legislation, search_legislation, ask_pipeworx, polymarket_*). Minor deviations like entity_profile, bet_research, and recent_changes are noun-phrase style rather than verb_noun, but there is no camelCase mixing or chaotic convention.

Tool Count1/5

A server named 'Legislation Uk' has 35 tools, only 4 of which relate to UK legislation; the rest are Pipeworx data-platform, prediction-market, memory, and subscription utilities. This is an extreme mismatch between the tool count and the server's apparent purpose.

Completeness4/5

The UK legislation portion covers the core read workflow well: search_legislation finds a statute, get_legislation returns metadata, and get_legislation_text/get_legislation_section provide full or section-level text with versioning. Minor gaps exist, such as no dedicated amendment-history or cross-version diff tool, but there are no dead ends for typical lookups.

Resources