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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").

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive, and open-world. The description adds valuable behavioral details: parallel fan-out to multiple sources, GDELT→GNews fallback on rate limit/5xx, USPTO soft-fail due to sunset, and return structure (grouped changes, total count, citation URIs). No contradiction.

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 not purely concise—it includes many query examples and details—but every sentence adds value. It front-loads common use cases, making it easy for an agent to understand quickly. Slightly longer than necessary but well-structured.

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 data sources, fallback, soft-fail) and the absence of an output schema, the description is remarkably complete. It covers parameter syntax, data source behavior, and return format, leaving no ambiguity for correct invocation.

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 descriptions cover 100% of parameters with clear explanations. The description adds extra value by providing relative shorthand examples for 'since' (e.g., '7d', '30d', '1y') and a typical usage note ('Use "30d" or "1m" for typical monitoring'). While schema already does well, the description enriches understanding.

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 defines the tool as a change feed for companies over a time window, aggregating from SEC EDGAR, GDELT/GNews, and USPTO. It explicitly distinguishes itself from the sibling tool 'entity_profile' for static profiles.

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 provides concrete query examples (e.g., 'What's new with X') and directly tells the agent to use 'entity_profile' when a static profile is needed instead of recent changes.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all serve similar query routing). Tools from unrelated domains (UK Gazette, Polymarket betting, AI visibility checks) are mixed together, making it hard for an agent to distinguish which tool to use for a given task.

Naming Consistency1/5

Naming is chaotic: some tools use descriptive phrases with underscores (gazette_deceased_estates, polymarket_arbitrage), others use generic verbs (remember, recall, forget), and some include version or mode indicators (ask_pipeworx_beta, scan_competitor_ai_presence). No consistent pattern across the set.

Tool Count2/5

With 36 tools, the server is overstuffed for its purported focus on the UK Gazette. The majority of tools (Polymarket, Pipeworx general, AI visibility, etc.) are unrelated to the server's name, making it feel like a bundling of many services into one, which is excessive for a coherent tool set.

Completeness2/5

For a server named 'Uk Gazette', there are only a handful of Gazette-specific tools (gazette_search_notices, gazette_insolvency_notices, etc.), while the rest cover unrelated domains. This leaves obvious gaps for Gazette-related tasks (e.g., no tool for searching particular notice types or filtering by edition), despite the large tool count.