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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 5,718 tools across 1496 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 readOnly, openWorld, idempotent, and non-destructive traits. The description adds valuable behavioral context beyond annotations: it routes to a large tool network, fills arguments automatically, returns structured answers with stable citation URIs, works on every tier, and is a single fast call. No contradiction with 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 long but front-loaded with the key directive ('PREFER OVER WEB SEARCH') and packed with actionable routing guidance, examples, and alternatives. Every sentence serves a purpose, though some repetition like 'START HERE' and 'default entry point' could be tightened.

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?

Given the tool's routing complexity and no output schema, the description still explains what the agent gets back: a structured answer with stable pipeworx:// citation URIs. It covers scope, trigger phrases, examples, tier behavior, and sibling tool boundaries, making it complete enough for confident 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 schema already documents the single question parameter plus aliases. The description reinforces that free-form natural language is accepted and gives examples, but it does not add substantial parameter-level semantics beyond what the schema provides, 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 names a specific action—routes questions to one of 5,714 tools across verified sources and returns structured answers with stable pipeworx:// citation URIs. It also differentiates itself from siblings by positioning ask_pipeworx as the default entry point and explicitly 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 gives explicit when-to-use guidance: prefer it over web search for factual/current/historical questions, and it lists trigger phrases plus concrete examples. It also states when to step up to ask_pipeworx_grounded or deep_research, and clarifies that breaking-news style questions are already handled here.

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 tools have blurry boundaries: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (beta is explicitly 'exactly' the stable version), and ai_visibility_check vs scan_competitor_ai_presence is a single-vs-batch duplicate. The six polymarket_* tools are differentiated by long descriptions, but their overlapping concerns (edges, arbitrage, fill risk, spread) would frequently misroute an agent, and discover_tools vs suggest_questions also compete.

Naming Consistency3/5

Names follow two coexisting conventions: verb_noun for actions (get_data, resolve_entity, validate_claim) and domain-prefixed families (polymarket_*, pipeworx_*, ask_pipeworx_*). Within each family the pattern is consistent, but mixing the two styles across the set, plus outliers like generate_llms_txt and bare verbs (remember, forget, recall), makes the overall scheme feel uneven though still readable.

Tool Count2/5

34 tools is well past the 'heavy' threshold and the count is not justified by the server's stated identity: a server named 'Statec Lu' (Luxembourg statistics) contains only 3 STATEC tools buried among general data-platform, prediction-market, AI-visibility, npm-scanning, and memory utilities. The sprawling, multi-domain surface would be more coherent split into separate servers.

Completeness3/5

The STATEC subset is complete (list_dataflows → dataflow_structure → get_data forms a full browse/fetch lifecycle), and the broader research surface covers entity resolution, grounded answers, comparison, claim verification, and subscription/alert/memory management. However, the overall domain is incoherent—a STATEC server missing nothing for statistics but carrying 31 unrelated tools—and there are notable gaps such as no tool to directly fetch a pipeworx:// citation URI and no execution side for the extensive Polymarket analysis tools.