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zippopotam

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

A4.2/5.0
Behavior4/5

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

Annotations already establish the tool as read-only and idempotent. The description adds useful behavioral context beyond this, such as returning top-N tools with full schemas and curated examples, and that no second schema lookup is needed. This gives the agent a clear expectation of the tool's output behavior.

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 succinct and front-loaded with the core purpose. The long domain list is informative rather than wasteful, and the additional sentences about return behavior and when to call it earn their place. It is not overly verbose.

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?

For a discovery tool with no output schema, the description thoroughly explains what is returned (top-N tools with names, descriptions, full input schemas), that results are directly callable, and when to use the tool. It also covers the input style ('describing the data or task'). This is complete for the tool's complexity.

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 description coverage is 100%, with all six parameters documented, including aliases and the default/max values for limit. The description's mention of 'top-N' reinforces the limit concept but does not add much beyond what the schema already provides. The baseline score of 3 is appropriate here.

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 opens with a specific verb and resource: 'Find tools by describing the data or task.' It clearly distinguishes this tool from siblings by positioning it as the tool-discovery entry point, especially with 'Call this FIRST when you have many tools available.' The scope is explicit and unambiguous.

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?

The description provides clear when-to-use guidance: 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available.' It also gives an exclusion ('not just one answer'), though it does not explicitly name alternative sibling tools.

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 purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, and bet_research all route questions to the same underlying engine, and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The polymarket_* family also has many closely-related entry points, though descriptions do help differentiate them.

Naming Consistency4/5

Names consistently use snake_case with descriptive verb-first patterns (ask_, lookup_, scan_, validate_, resolve_, subscribe) and a clear polymarket_ family prefix. Minor inconsistency exists between lookup_city/lookup_zipcode and resolve_entity, and between noun-style names like entity_profile vs verb-style names like compare_entities, but the overall style is predictable.

Tool Count2/5

33 tools is heavy for a single server, and multiple could be consolidated: the ask_pipeworx variants and deep_research largely overlap, and the memory/subscription categories could be collapsed. For a data-platform gateway the breadth is arguably justified, but the visible redundancy makes the surface feel bloated rather than well-scoped.

Completeness4/5

The core domains are well covered: question answering has multiple modes, entity lookup has resolution and profiling, prediction markets have research/edge/arb/fill-risk coverage, and the memory (remember/recall/forget) and subscription (subscribe/list/unsubscribe/recent_alerts) lifecycles are complete. Minor gaps exist such as no direct tool to fetch a pipeworx:// record by URI, relying instead on MCP resources.

Resources