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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

A4.4/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable behavioral context: returns top-N tools with full schemas ready to call, and accepts multiple aliases. No contradictions.

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?

The description is front-loaded with purpose and usage, but slightly verbose with the list of domains. However, every sentence adds value, and it is well-structured for an agent to parse.

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, the description fully explains the return: 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)'. It covers what the agent needs to know for a discovery tool with 6 parameters, no gaps.

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%, so baseline is 3. The description adds value by summarizing aliases ('Accepts task, q, description, search as aliases') and providing examples in the schema. This compensates with clarity 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?

The description explicitly states 'Find tools by describing the data or task' and lists numerous domains (SEC filings, financials, etc.), making the purpose clear. It distinguishes from siblings by emphasizing it is for browsing the tool set, especially 'Call this FIRST when you have many tools available and want to see the option set'.

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?

Provides clear guidance on when to use: 'when you need to browse, search, look up, or discover what tools exist'. It also suggests using it first to see options. While it doesn't explicitly state when not to use, the context and directive are strong enough for an agent.

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

A4.1/5.0
Disambiguation3/5

Several tools overlap in purpose (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim all handle factual queries), which could confuse an agent. However, detailed descriptions help differentiate them, so the confusion is moderate.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern (e.g., resolve_entity, compare_entities). A few irregular verbs (forget, recall, remember) and diverse prefixes (pipeworx_, polymarket_) lower consistency slightly.

Tool Count3/5

33 tools is high but each serves a distinct purpose within a broad domain (data querying, prediction markets, security, memory, etc.). The number feels slightly excessive for a single server, but not extreme.

Completeness4/5

The tool surface covers many aspects of data retrieval, prediction market analysis, and security checks. Minor gaps exist (e.g., no dedicated WHOIS or CVE lookup), but core workflows are well-supported.

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