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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 5,724 tools across 1497 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
Behavior4/5

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

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds useful behavioral context: routing mechanics, argument filling, citation URI returns, and the 'one fast call' performance trait. It does not mention failure modes or unsupported question types, but the annotation coverage reduces the burden.

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 directive ('PREFER OVER WEB SEARCH') and organized with domains, usage triggers, examples, and escalation paths. It is somewhat long with minor redundancy ('START HERE', 'default entry point', 'works on every tier'), but each sentence earns its place in guiding tool selection.

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?

There is no output schema, but the description explains the return format (structured answer with pipeworx:// citation URIs), covers when to use the tool, and specifies exactly when to step up to siblings. For a general-purpose question tool with strong annotations, this is complete enough for an agent to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and all six parameters are aliases for the same free-text question. The description adds semantic guidance by enumerating domains, trigger phrases, and example questions, which meaningfully helps the agent formulate a good value for the single open-ended parameter.

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 identifies the tool as a question router that selects from 5,724 tools and returns structured answers with citation URIs. It also explicitly differentiates itself from ask_pipeworx_grounded and deep_research, so an agent can distinguish siblings without inspecting schemas.

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', 'START HERE') and precise conditions for escalating to alternatives: ask_pipeworx_grounded for hallucination-resistant single answers, deep_research for broad/multi-part questions. It also notes that breaking-news queries are already handled by this tool.

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

Multiple tool families blur together: ask_pipeworx, ask_pipeworx_beta (currently identical by admission), ask_pipeworx_grounded, and deep_research all route to the same 5,721 tools, and the six polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread, bet_research) heavily overlap on prediction-market analysis. The descriptions are verbose but an agent would struggle to reliably pick the right one without reading thousands of words.

Naming Consistency3/5

All names are snake_case, but conventions vary: verb_noun (get_artist, search_album, list_subscriptions), noun-first (polymarket_edges, entity_profile, recent_alerts), bare verbs (remember, forget, recall, subscribe), and vendor prefixes (pipeworx_*, polymarket_*). More importantly, the server is named Theaudiodb yet almost none of the tool names reflect music, making the naming misleading about the server's actual scope.

Tool Count2/5

35 tools is over the threshold for a well-scoped server, and the sprawl is severe: 4 music tools, roughly 20 data-research tools, 6 prediction-market tools, memory utilities, subscription management, npm scanning, and AI-visibility checks. This is not one coherent server but several servers' tool sets bolted together, with no unifying purpose that justifies the count.

Completeness2/5

For a server named Theaudiodb, coverage is thin: search_artist, search_album, get_artist, and get_album_tracks exist, but there is no search_track, no get_album metadata by ID (only its tracks), no trending/browse-by-genre, and get_artist requires an ID only obtainable by searching first. Meanwhile the 31 non-music tools suggest the real domain is actually Pipeworx data research, making the overall surface feel like an incoherent mix where neither domain is fully covered.