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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").

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare readOnly/idempotent, and the description adds substantial behavioral context: fans out to three sources, GDELT preferred with GNews fallback on rate-limit/5xx, USPTO patent source sunset May 2025 with soft-fail, and grouped output structure with citation URIs. No contradiction with annotations.

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 dense paragraph but every sentence adds value: example queries, source fan-out, parameter format, output shape, and alternative tool. It is long but not wasteful; however, a bulleted breakdown would improve scannability. Still far above average.

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?

With no output schema, the description explicitly states return shape (changes[], total_changes, pipeworx:// URIs). It covers failure modes (GDELT fallback, USPTO sunset), parameter syntax, and source scope. Ideal for a complex multi-source tool with no structured output definition.

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?

Schema coverage is 100%, but description adds meaningful examples: `since` accepts ISO date or relative shorthand ('7d', '30d', '3m', '1y') with typical usage '30d' or '1m'; `value` can be ticker or zero-padded CIK. This goes beyond the schema's terse descriptions and helps correct invocation.

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 opens with concrete example queries ('What's new with X', 'latest on Y') and states it's a 'change feed for a company in the last N days/weeks/months in ONE parallel call'. It clearly differentiates from sibling `entity_profile` by contrasting 'static profile' vs. change feed. Specific verb+resource+scope.

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 when-to-use context via example intents and window handling. It names the exact alternative: 'Use entity_profile instead when you want the static profile... regardless of window.' Also describes internal fallback logic (GDELT→GNews) and soft-failure for USPTO, guiding expectations.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve as entry points for data questions, and ask_pipeworx_beta currently behaves identically to ask_pipeworx. Entity-focused tools (entity_profile, compare_entities, recent_changes, ai_visibility_check, scan_competitor_ai_presence) also blur together even with lengthy descriptions.

Naming Consistency4/5

All tools use lowercase snake_case, which is consistent and readable. There is some variation between verb-first names (discover_tools, resolve_entity) and noun-first names (entity_profile, polymarket_arbitrage), plus the ask_pipeworx variant family, but the pattern is predictable overall.

Tool Count2/5

35 tools is heavy, and the scope sprawls far beyond the 'Rba' server name: only 4 tools relate to the Reserve Bank of Australia, while the rest cover a universal data router, prediction markets, memory, subscriptions, AI visibility, npm scanning, and more. Several meta-tools (ask_pipeworx, deep_research, discover_tools, suggest_questions) duplicate the discovery/routing role, making the count feel inflated.

Completeness3/5

For the RBA-specific subdomain, coverage is solid: directory lookup, series fetching, cash rate, and exchange rates. For the broader data-research domain most tools imply, coverage is quite comprehensive (routing, grounded answers, entity resolution, fact-checking, monitoring, memory), but the server's stated identity is unclear, and the beta duplicate tool adds noise rather than filling a real gap.