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Arcgis Maricopa

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

A4.9/5.0
Behavior5/5

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

Goes beyond the read-only and idempotent annotations by disclosing multi-source fan-out (SEC, GDELT/GNews, USPTO), fallback triggers (rate limited/5xx), soft-failure due to PatentsView API sunset, and the exact return shape (changes[], total_changes, citation URIs). This gives the agent full visibility into side effects and output behavior.

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?

While the description is longer than average, each segment serves a distinct purpose: user examples, source breakdown, parameter clarification, output format, and alternative tool. The organization into clauses with clear logical flow means no sentence is wasted, justifying the length.

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 having no output schema, the description fully covers invocation, input formats, output structure, failure modes, and alternatives. It provides all the information an agent needs to select and correctly invoke the tool, and to interpret the result, making it contextually complete.

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 already describes all 3 parameters at 100% coverage. The description adds value by providing concrete `since` format examples ('7d', '30d', '3m', '1y') and typical usage guidance ('30d' or '1m'). This elevates it above baseline without fully re-explaining each parameter.

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 identifies the tool as a 'change feed for a company' returning recent filings, news, and patents. It opens with diverse user query examples and explicitly distinguishes itself from sibling entity_profile ('Use entity_profile instead when you want the static profile'), making the purpose unmistakable.

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 cues ('What's new with X', 'latest on Y') and an explicit alternative (entity_profile) for static data. Also gives concrete parameter guidance ('Use "30d" or "1m" for typical monitoring') and explains fallback behavior between GDELT and GNews.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Arcgis Maricopa toolsInspect
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TDQS

A3.8/5.0
Disambiguation3/5

Many tools have distinct purposes, but there is overlap within the Pipeworx family (ask_pipeworx vs ask_pipeworx_grounded) and Polymarket tools (bet_research, polymarket_edges, etc.). Descriptions are detailed and help differentiate, but the sheer number of tools from different domains can cause an agent to select the wrong one for a given task.

Naming Consistency2/5

Naming is highly inconsistent: some tools follow verb_noun (ask_pipeworx, compare_entities), others are nouns (layer_info, entity_profile), and some have prefixes (pipeworx_trending, polymarket_arbitrage). There is no uniform pattern, making the set feel chaotic.

Tool Count2/5

33 tools is far too many for a server named 'Arcgis Maricopa', which only has 3 GIS-specific tools. The remaining tools are from unrelated domains (polymarket betting, general Pipeworx queries, utilities), making the tool set bloated and unfocused for its stated purpose.

Completeness3/5

For the ArcGIS domain, the set is minimal (only search, schema, and query) and lacks management or analysis tools. However, the broader toolset covers many data domains (finance, drugs, prediction markets), but with gaps like no update/delete operations for the GIS data. The overall coverage is mixed.

Resources