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Glama

Washington State Open Data

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.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds that results include full schemas and examples, that tools are ready to call without second lookup. No contradictions. Some additional behavioral context beyond 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?

Description is fairly long but dense with useful information. Front-loaded with purpose and usage. Could trim domain list slightly, but every sentence adds value.

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, description fully explains return format: top-N tools with names, descriptions, and full input schemas with curated examples. Explains readiness to call. Covers all necessary context for a discovery tool.

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 descriptions for all 6 parameters. Description mentions aliases but schema already defines them. Examples are provided in schema schema. Description adds no new semantic meaning beyond what schema provides.

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 'Find tools by describing the data or task' and lists dozens of domains. Differentiates from sibling tools by being a discovery/search tool. Returns ready-to-call results with schemas and examples.

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?

Explicitly says 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available'. Tells when not appropriate (not just one answer). Clearly distinguishes from direct query tools.

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

All Washington State Open Data toolsInspect
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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have distinct purposes with detailed descriptions, but there is overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, all serving data retrieval. Also, prediction market tools (e.g., bet_research, polymarket_arbitrage) are closely related, causing potential ambiguity.

Naming Consistency2/5

Naming conventions are inconsistent: mostly snake_case (ask_pipeworx, entity_profile) but includes camelCase (ai_visibility_check). No clear pattern, mixing verb_noun and other structures.

Tool Count1/5

33 tools is excessive for a server named 'Washington State Open Data'; only 3 tools (datasets, metadata, query) are directly relevant, while the rest are unrelated Pipeworx/Polymarket tools. The count does not match the server's stated scope.

Completeness1/5

The tool set severely misaligns with the server name: it covers general data and prediction markets rather than Washington State Open Data. Only basic query and metadata tools exist for the stated domain, leaving many common dataset operations (e.g., CRUD) missing and providing entirely irrelevant functionality.

Resources