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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 5,798 tools across 1517 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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already convey readOnly, openWorld, and idempotent behavior. The description adds useful behavioral context: it routes across thousands of tools, fills arguments automatically, returns structured answers with citation URIs, and routes breaking-news questions to live news packs. There is no contradiction with the 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?

The description is dense and information-rich, with a clear flow: primary use case, mechanism, trigger phrases, examples, and alternative routing. It is longer than average, but nearly every sentence adds useful routing or selection guidance. The example list is somewhat long but valuable for grounding an agent's question formulation.

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?

For a routing tool with no output schema, the description covers purpose, scope, trigger phrases, examples, alternatives, and citation-return behavior. The main gap is that the sibling ask_pipeworx_beta is not mentioned or differentiated, leaving some ambiguity about when to choose the beta variant. Overall, though, the definition gives enough context for correct invocation in most cases.

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?

The input schema has 100% description coverage, documenting the main 'question' parameter and all five aliases. The description reinforces this with examples and natural-language trigger guidance, but it does not add parameter-level meaning beyond what the schema already provides, so the baseline score 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 opens with 'PREFER OVER WEB SEARCH' and defines the tool as a router that sends questions to the right one of 5,798 tools across 1,517 sources, fills arguments, and returns structured answers with stable pipeworx:// citation URIs. This is a specific verb-plus-resource description that clearly differentiates the tool from web search and sibling research tools.

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?

It explicitly states when to use the tool: for current or historical factual data, with example trigger phrases like 'what is', 'look up', 'find', and 'get the latest'. It also names alternatives — ask_pipeworx_grounded for specific-source citations and deep_research for broad/multi-part questions — and says 'START HERE for most questions.' This is strong when-vs-when-not 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

A3.9/5.0
Disambiguation3/5

Several tools overlap in purpose: ask_pipeworx_beta is explicitly identical to ask_pipeworx today, and the polymarket_* family plus bet_research all touch prediction-market analysis. The descriptions are extremely detailed and mostly disambiguate, but an agent must rely on very long text to avoid misselection.

Naming Consistency3/5

Names are almost all snake_case and readable, but the pattern is mixed: some are verb-first (resolve_entity, list_subscriptions), some noun-first (entity_profile, polymarket_edges), and some are one-word verbs (remember, forget). The ask_pipeworx_* and recent_* prefixes are consistent, but there is no single verb_noun convention throughout.

Tool Count2/5

33 tools is well over the 25+ threshold, especially for a server named 'Csv' that contains only two CSV-specific tools. The rest spans several unrelated domains: data research, prediction markets, subscriptions, memory, AI visibility, and package scanning. The set feels like multiple servers bundled together rather than one well-scoped surface.

Completeness4/5

As a broad data-research platform, coverage is strong: lookup, grounded answers, deep research, entity resolution, profiles, comparisons, fact-checking, subscription lifecycle, and memory persistence are all present. Minor gaps exist, such as no direct fetch tool for pipeworx:// citation URIs and no subscription-update tool, but most workflows have no dead ends.