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Ask Pipeworx

ask_pipeworx
Read-onlyIdempotent

PREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring authoritative structured data with citations. Routes the question to the right one of 5,728 tools across 1498 verified sources, fills arguments, returns the structured answer with stable pipeworx:// citation URIs. Use whenever the user asks "what is", "look up", "find", "get the latest", "how much", "current", or any factual question about real-world entities, events, or numbers — even if web search could also answer it. Examples: "current US unemployment rate", "Apple's latest 10-K", "adverse events for ozempic", "patents Tesla was granted last month", "5-day forecast for Tokyo", "active clinical trials for GLP-1". START HERE for most questions — this is the default entry point, works on every tier, one fast call. Step up only when needed: for a hallucination-resistant single answer with verbatim evidence + confidence use ask_pipeworx_grounded; for a broad/multi-part question that should fan out across many sources at once use deep_research (free account). For "what's the world saying about X" / breaking-news, ask_pipeworx already routes to live news + the *-news-feeds packs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for question.
textNoAlias for question.
inputNoAlias for question.
queryNoAlias for question.
promptNoAlias for question.
questionYesYour question or request in natural language. Accepts query, q, prompt, text, input as aliases.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already establish read-only, open-world, idempotent behavior, and the description adds meaningful behavioral detail: dynamic routing across thousands of tools, automatic argument filling, structured response format, stable pipeworx:// citation URIs, and single-call execution. This all goes beyond what annotations alone convey.

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 long but dense, front-loading the key message (PREFER OVER WEB SEARCH) and then giving concrete trigger phrases, examples, and escalation paths. A few phrases are slightly redundant (e.g., 'START HERE' and 'default entry point'), but overall the length serves the tool's broad selection purpose.

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 broad routing tool with no output schema, the description tells the agent what it does, when to use it, when to use alternatives, what kinds of questions it handles, and what the response will include. This is sufficient for both selection and invocation.

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% and the single semantic parameter is already documented as a natural-language question with aliases. The description reinforces this with examples, but does not add substantially new meaning beyond the schema, so the baseline of 3 is appropriate.

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's role: it routes a natural-language question to one of 5,724 tools across 1,497 sources and returns structured answers with citation URIs. It also distinguishes itself from web search and from sibling tools like ask_pipeworx_grounded and deep_research.

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?

The description explicitly says to prefer this over web search, gives trigger phrases and example questions, designates it as the default entry point, and names exact conditions for escalating to ask_pipeworx_grounded or deep_research. This is unusually complete routing guidance.

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
Disambiguation3/5

While many tools have distinct purposes, there is overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as multiple Polymarket and entity-related tools. Descriptions are detailed but could confuse agents on which tool to use for a specific query.

Naming Consistency3/5

Most tool names use snake_case and many start with verbs, but there is inconsistency with noun-starting names like entity_profile, layer_info, and pipeworx_feedback. No strong verb_noun or other consistent pattern across the set.

Tool Count3/5

With 33 tools, the count is relatively high but could be justified for a broad data platform. However, given the server name 'Arcgis Sanjose', the number seems excessive as most tools are unrelated to ArcGIS geospatial functions.

Completeness2/5

The tool set is severely incomplete for the implied ArcGIS San Jose domain, with only 3 tools (search_datasets, layer_info, query_layer) supporting that purpose. The rest are from the Pipeworx ecosystem, creating a mismatch between server name and actual functionality.