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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

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds useful behavioral context: it routes, fills arguments, and returns citation URIs rather than directly producing a static answer. This goes beyond what annotations alone communicate and does not contradict them.

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

Conciseness2/5

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

The opening guidance is useful and front-loaded, but the description contains a repeated "START HERE for most questions" block with the same examples appearing multiple times. This makes it unnecessarily long and not every sentence earns its place.

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 broad routing tool with rich annotations and full schema coverage, the description explains the output shape (structured answer with stable citation URIs), provides use cases and examples, and names alternatives. It could describe exact response fields, but that is not essential for correct 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%, so the schema fully documents the question parameter and its aliases. The description reinforces that the input is a natural-language question and gives examples, but it does not add significant parameter-level meaning beyond the schema.

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 the tool's function: it routes a question to one of 5,743 tools across 1,500 verified sources, fills arguments, and returns a structured answer with pipeworx:// citation URIs. It also distinguishes itself from siblings like ask_pipeworx_grounded and deep_research, so an agent can identify which tool is which.

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 explicitly says to prefer this tool over web search for certain data categories and lists trigger phrases like "what is", "look up", "find", and "get the latest". It also gives clear guidance on when to step up to ask_pipeworx_grounded or deep_research, making the decision boundary explicit.

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

Several tools are functionally near-identical: ask_pipeworx_beta is explicitly a duplicate of ask_pipeworx (descriptions say they 'currently match exactly'), and ask_pipeworx_grounded differs only in answer-extraction mode. The six Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) heavily overlap on edge-finding and fill-risk, and ai_visibility_check duplicates scan_competitor_ai_presence's per-entity probing. Agents will frequently misselect among these.

Naming Consistency4/5

Naming is consistently snake_case with a mostly verb_noun pattern (get_post, top_launches, subscribe, forget, validate_claim, resolve_entity). Minor deviations exist where nouns lead (entity_profile, recent_changes, recent_alerts, bet_research), and polymarket_* names use a domain-prefix style rather than pure verb_noun, but the overall pattern is predictable and readable.

Tool Count2/5

33 tools is at the heavy end, and the count is badly mismatched to the server's stated identity: it is named 'Producthunt' yet only 2 of 33 tools (get_post, top_launches) are Product Hunt related — the rest are Pipeworx data lookup, prediction-market, memory, and subscription tools. The redundancy (duplicate ask_pipeworx_beta, overlapping polymarket tools) inflates the count without adding surface.

Completeness2/5

Judged against the Product Hunt domain implied by the server name, the surface is severely incomplete: coverage is limited to list-top-launches and get-one-post, with no search, users, comments, votes, collections, or categories — and no way to act on Product Hunt data at all. As a general Pipeworx data platform the coverage is broader, but for the named purpose there are large gaps that will force agent failures.