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Country State City

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").

TDQS

A5/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent), the description details fan-out to multiple sources, fallback from GDELT to GNews, soft-fail for USPTO, and the inclusion of 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and concise, with every sentence providing necessary information. It covers purpose, usage, parameters, and disambiguation without redundancy, making it easy for an agent to parse.

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 behavior, flexible date input) and the absence of an output schema, the description adequately explains the return structure (changes grouped by source, total_changes count, citation URIs) and directs to entity_profile for alternative needs.

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?

Although schema coverage is 100%, the description adds significant value by explaining acceptable formats for 'since' (ISO date or relative shorthand) with examples, and clarifying that 'value' accepts tickers or CIK numbers. It also notes that 'type' currently only supports 'company'.

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 provides a 'change feed for a company in the last N days/weeks/months in ONE parallel call', listing specific data sources and example queries. It explicitly distinguishes from the sibling tool entity_profile, ensuring the agent can correctly differentiate.

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 explicit when-to-use examples ('What's new with X', 'latest on Y') and when-not-to-use by directing to entity_profile for static profiles. This clear guidance helps the agent select the appropriate tool.

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

A3.7/5.0
Disambiguation2/5

Several tools overlap enough to cause misselection: ask_pipeworx and ask_pipeworx_beta are functionally identical right now, ask_pipeworx_grounded and validate_claim both handle factual lookup/verification, and ai_visibility_check/scan_competitor_ai_presence are near duplicates in scope. The country/state/city tools are distinct but sit in a pile of unrelated Pipeworx tools, adding confusion.

Naming Consistency3/5

All names are lower_snake_case and families like polymarket_* and ask_pipeworx* help group tools, but the verb_noun convention is inconsistent: entity_profile, deep_research, recent_alerts, and pipeworx_trending are noun phrases, while remember/forget/subscribe are bare verbs. It is readable but not a predictable pattern.

Tool Count2/5

34 tools is above the practical ceiling for a focused MCP server, and the mismatch is severe: only 3 tools match the 'Country State City' name while 31 belong to a broad Pipeworx platform. A geographic server would need roughly 3-6 focused tools; this surface is bloted.

Completeness2/5

For the stated Country State City domain, list_countries/get_states/get_cities provide the basic hierarchy, but there is no city search, country/state detail lookup, or attribute discovery beyond the three list endpoints, making the useful geographic surface thin. For the Pipeworx domain the coverage is broader, but that confirms the identity mismatch and obscures the server's actual purpose.

Resources