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Glama

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 5,767 tools across 1506 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

A4.6/5.0
Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail beyond that: it fills arguments automatically, returns stable pipeworx:// citation URIs, and routes to live news when relevant. There is no contradiction with any annotation.

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 the most important instruction and uses examples and alternatives efficiently. It is slightly long and somewhat redundant between 'PREFER OVER WEB SEARCH' and 'Use whenever', so it doesn't quite earn a 5, but every major section clearly earns its place.

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 high-complexity router tool with no output schema, the description is complete: it explains what inputs to provide, what the tool does internally, what kind of answer is returned, and when to choose a sibling tool instead. An agent has enough context to invoke it correctly in most situations.

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: all six properties are documented as aliases for the single 'question' parameter. The description doesn't need to add parameter details, and it only reinforces the natural-language input expectation with examples. Baseline 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 what the tool does: it routes a natural-language question to one of 5,767 tools across 1,506 verified sources and returns a structured answer with citation URIs. It also distinguishes itself from siblings by presenting itself as the default ('START HERE for most questions') and naming ask_pipeworx_grounded and deep_research as alternatives.

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 is explicit about when to prefer it over web search, when to use it for factual questions, and even provides alternatives: ask_pipeworx_grounded for grounded answers, deep_research for broad/multi-part questions, and news-feeds packs for breaking news. This gives an agent clear routing guidance with no ambiguity.

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

B3.1/5.0
Disambiguation1/5

The toolset is overwhelmingly fragmented: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical entry points; polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk heavily overlap; and ai_visibility_check vs scan_competitor_ai_presence cover the same task. The five actual Wiktionary tools are distinct but are lost among dozens of unrelated research and prediction-market tools, making selection highly ambiguous.

Naming Consistency3/5

All names use snake_case and several logical prefixes (ask_pipeworx, polymarket_, pipeworx_) create local patterns. However, the naming mixes noun-style commands (definition, etymology, pronunciations, summary) with verb-style commands (search, remember, forget, validate_claim), and no consistent verb_noun convention carries across the whole set.

Tool Count1/5

36 tools is already heavy, but the deeper problem is that only 5 tools actually belong to a Wiktionary server while 31 tools serve unrelated Pipeworx, Polymarket, memory, and marketing-audit functions. The count is wildly inappropriate for the declared server purpose.

Completeness2/5

The Wiktionary-relevant tools cover basic word lookup—search, summary, definition, etymology, pronunciations—but omit common dictionary operations like translations, usage examples, inflected forms, or random entries. The non-Wiktionary majority does not fill these gaps; it just makes the surface area incoherent and hard to reason about.