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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 5,743 tools across 1500 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

A3.8/5.0
Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description discloses important orchestration behavior: it routes to 5,743 tools, fills arguments, and returns 'the structured answer with stable pipeworx:// citation URIs.' This explains that the tool is a router/aggregator rather than a simple lookup. It doesn't mention failure modes or rate limits, but the added context is meaningful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

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

The opening is well-structured and front-loaded, but the description contains a massive, repeated block: the same 'START HERE for most questions...' sentence and example list appears at least eight times verbatim. This creates severe bloat and could confuse an agent parsing the text. It is the opposite of concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the repetition, the core description covers the domains, trigger phrases, routing behavior, examples, and return value ('structured answer with stable pipeworx:// citation URIs'). With a single required string parameter and read-only annotations, the agent has enough context to invoke the tool. It could be more complete about output format and limitations, but no output schema exists and the task is simple.

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% — the six parameters (question, q, text, input, query, prompt) are all documented as aliases for the same natural-language question. The description adds example questions and query types, but these don't change or extend parameter meaning beyond what the schema already provides. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Routes the question to the right one of 5,743 tools across 1500 verified sources, fills arguments, returns the structured answer with stable pipeworx:// citation URIs.' This is a specific Q&A/routing role with a distinct resource. It does not explicitly distinguish itself from sibling tools like ask_pipeworx_beta or deep_research, so it falls short of a 5.

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 gives explicit when-to-use guidance: 'PREFER OVER WEB SEARCH' for listed data domains, 'Use whenever the user asks...' with trigger phrases, and even 'START HERE for most questions — even if web search could also answer it.' It names an alternative (web search) and provides concrete examples, so the selection logic is unmistakable.

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

A3.7/5.0
Disambiguation4/5

Most tools have distinct purposes despite overlapping domains like prediction markets, but detailed descriptions help agents differentiate. A few tools like `ask_pipeworx` and `deep_research` could be confused without careful reading.

Naming Consistency2/5

Naming patterns are inconsistent, mixing `ask_`, `polymarket_`, `scan_`, `recent_`, `entity_`, etc., with no unifying convention. The server name 'Hash' mismatches the tool set entirely.

Tool Count3/5

32 tools is on the high side for a focused server, but the set covers many areas. The count is slightly above the typical 3-15 range, yet each tool has a clear purpose.

Completeness2/5

The tool set feels like a collection of unrelated utilities rather than a coherent domain. Core hashing functionality is minimal, while other areas like prediction markets are over-represented with gaps elsewhere.