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Data Usdot

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

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint), description explains it returns top-N relevant tools with full schemas and curated examples, ready to call directly. 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.

Conciseness4/5

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

Description is informative and well-structured, front-loading purpose. Slightly verbose but justified by content density.

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 no output schema, description fully explains return values (names, descriptions, schemas, examples, ready to call) and covers parameter limits. Complete for a discovery tool.

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 has 100% coverage with descriptions. Description adds contextual examples (e.g., 'analyze housing market trends') and notes aliases, providing extra guidance beyond 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 finds tools by describing data or task, lists specific domains, and distinguishes itself from siblings as a discovery tool that returns ready-to-call results with full schemas.

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 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' Provides clear when-to-use context.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping or near-identical purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are one base query flow with different flavors, while entity_profile, compare_entities, and recent_changes all overlap on company information. The Polymarket family and the discovery/onboarding tools (discover_tools, suggest_questions, pipeworx_trending) also create boundary confusion despite good descriptions.

Naming Consistency3/5

The naming is consistently snake_case and mostly readable, but it mixes verb_noun tools (compare_entities, resolve_entity, validate_claim) with noun-phrase tools (entity_profile, polymarket_arbitrage, pipeworx_trending, datasets, metadata). The ask_pipeworx variants use a beta/grounded suffix pattern that is not applied uniformly across the other tool families.

Tool Count2/5

34 tools is well above the 25+ threshold and feels like several servers merged into one: US DOT catalog access, a generic Pipeworx data router, prediction-market tools, memory/subscription management, AI-visibility checks, and meta/discovery utilities. Many tools could be consolidated (the three ask_pipeworx variants, the five Polymarket tools, and the discovery trio).

Completeness3/5

The core data lifecycle is broadly covered: catalog search, metadata, querying, natural-language lookup, grounded verification, entity resolution, entity profiles, comparison, research, subscriptions, and memory all have working paths. However, the server is named around US DOT data but only datasets/metadata/query are DOT-specific, and the rest is an unrelated general-purpose data and prediction-market toolkit, leaving the stated domain feeling incomplete.

Resources