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Data Delaware

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?

Annotations already indicate safe read-only operation. Description adds: returns top-N tools with full schemas, ready to call directly. No contradictions with annotations. Provides output behavior details 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?

Front-loaded with core purpose, then domains, then output details, then usage context. Slightly long but every sentence adds value. Could be more concise without losing clarity.

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?

Comprehensive for a discovery tool: covers purpose, when to use, output format (top-N with schemas), aliases, domain examples. No output schema needed; description sufficiently describes return. Handles complexity well.

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 coverage is 100%, baseline 3. Description adds value by listing example domains (SEC filings, FDA drugs, etc.) to guide natural language queries. Also mentions aliases. Sufficient adds meaning 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?

Clearly states 'Find tools by describing the data or task.' Specifies verb (find) and resource (tools). Distinguishes from siblings by positioning as a first-call for tool discovery, unlike other tools that return data directly.

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).' Implies alternatives (other tools) and provides clear context for when to use.

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

Many tools have overlapping purposes, e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route queries to the same data sources with only subtle differences. Similarly, bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_edge_tracker all analyze prediction markets, making it hard for an agent to pick the right one without deep reading of descriptions.

Naming Consistency3/5

Tool names follow a mix of patterns: some are verb_noun (generate_llms_txt, list_subscriptions), some noun_verb (ai_visibility_check, bet_research), and some are just nouns (datasets, metadata). The ask_pipeworx family has consistent prefixes but suffixes vary. Overall readable but inconsistent.

Tool Count2/5

34 tools is excessive for a coherent server. The server tries to be a Swiss Army knife covering data lookup, prediction markets, Delaware open data, memory, subscriptions, and misc tools like generate_llms_txt and scan_dependency. Many tools feel tacked on, and the count makes it unwieldy for an agent to navigate.

Completeness3/5

The server covers multiple domains thoroughly (data query via Pipeworx variants, prediction markets with arbitrage and edges, Delaware open data, memory, subscriptions). However, there are gaps: no tool for managing custom pipelines or for updating data. For the broad scope, it is decent but not fully comprehensive.

Resources