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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

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint; the description adds valuable behavioral details: parallel fan-out, source fallback logic, and soft-failure for patents. No contradictions.

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?

Every sentence earns its place, front-loaded with example queries, and efficiently covers sources, parameters, and return structure without redundancy.

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?

Despite no output schema, the description states return structure (changes[], total_changes, citation URIs). All three parameters are fully documented, and the tool's complexity is well-addressed.

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 the description adds significant meaning: relative time shorthand for 'since', zero-padded CIK format for 'value', and permissible 'type' values. Goes well beyond the schema.

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 concrete example queries. It distinguishes from the sibling 'entity_profile' by specifying when to use each.

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 (recent changes) and when-not-to (use entity_profile for static profile), along with fallback behavior (GDELT→GNews) and limitations (USPTO soft-fail).

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

A3.6/5.0
Disambiguation2/5

The set contains several tightly overlapping clusters: ask_pipeworx vs ask_pipeworx_beta (currently identical) vs ask_pipeworx_grounded, five polymarket_* tools with related purposes, and entity_profile vs compare_entities vs recent_changes covering similar company-research ground. The four game tools are distinct but swamped by the unrelated Pipeworx majority, making correct tool selection genuinely difficult.

Naming Consistency2/5

No coherent naming scheme spans the set: snake_case verb_noun (get_game, list_platforms, scan_dependency) coexists with verb_prefix descriptors (ask_pipeworx, generate_llms_txt), domain-prefixed nouns (polymarket_edges, pipeworx_trending), and bare verbs like recall and forget. Even within the Pipeworx cluster, styles vary unpredictably (ask_pipeworx vs pipeworx_feedback vs scan_competitor_ai_presence).

Tool Count2/5

35 tools is far too many for a server named Thegamesdb, where only 4 of 35 tools relate to the game database at all. The remaining 31 tools constitute a broad Pipeworx data platform with heavy internal overlap, making the surface feel bloated rather than well-scoped.

Completeness2/5

For the declared TheGamesDB domain, coverage is minimal: search, get-by-id, and list genres/platforms, with no per-platform game listings, images/artwork, or updates/refresh functionality. If the true domain is Pipeworx data access, the surface is fairly complete, but as presented under Thegamesdb there are major gaps and a severe identity mismatch.