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Arcgis Tucson

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns top-N most relevant tools with full schemas and examples, ready to call, no second lookup needed.

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?

Four sentences front-loaded with purpose, followed by domain list and output behavior. Every sentence adds value with no waste.

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 6 parameters, no output schema, and sibling tools list, the description explains what the tool does, when to use, and what it returns. It is complete for an agent to understand and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with full descriptions of each parameter including aliases. Description mentions aliases for query but adds no new semantics 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?

Description clearly states the verb 'Find tools' and resource 'by describing the data or task', listing many domains. It distinguishes from sibling tools which are for specific tasks like bet_research or deep_research.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Call this FIRST when you have many tools available and want to see the option set'. Implies not for single answers but no explicit when-not alternatives.

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
Disambiguation3/5

While individual tool descriptions are detailed and specific, the set includes overlapping tools like ask_pipeworx and ask_pipeworx_grounded, and several prediction market tools with similar purposes (bet_research, polymarket_edges, polymarket_arbitrage). The broad range of unrelated domains means many tools are distinct, but some pairs are ambiguous.

Naming Consistency2/5

Tool names use snake_case but follow no consistent pattern. Some are verb_noun (ask_pipeworx, query_layer), some noun_verb (ai_visibility_check, entity_profile), and some have inconsistent structure (discover_tools, recent_alerts). The mix of conventions reduces predictability.

Tool Count1/5

33 tools is excessive for a server named 'Arcgis Tucson', as only 3 tools relate to ArcGIS (search_datasets, layer_info, query_layer). The rest span completely unrelated domains (Pipeworx data, Polymarket, memory, npm scanning, etc.), creating a severe mismatch between server name and tool functionality.

Completeness3/5

Considering the actual tool surface (a diverse data retrieval and prediction market analysis set), it is reasonably complete for common lookups (SEC, FDA, economics, news, bets). However, it lacks web search and the ArcGIS tools are minimal. The absence of a cohesive domain makes completeness hard to judge, but for the implied data-retrieval purpose, it's passable.

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