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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 5,738 tools across 1499 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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/openWorldHint/idempotentHint, so no contradiction. The description adds useful behavioral detail: it routes to 5,724 tools across 1,497 sources, fills arguments, and returns stable pipeworx:// citation URIs, giving the agent an accurate mental model of the call's semantics.

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 and largely earns its length: the preference rule, routing behavior, examples, and sibling escalation path are all decision-relevant. It is slightly repetitive (e.g., 'PREFER OVER WEB SEARCH' and 'START HERE' overlap), but no sentence is pure filler.

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?

Despite no output schema, the description tells the agent what it will receive: a structured answer with stable pipeworx:// citation URIs. It also covers sibling routing, domain coverage, and tier/performance context ('works on every tier, one fast call'), making the tool complete enough to invoke correctly.

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 schema already documents 6 aliases for a single natural-language question parameter at 100% coverage, so the baseline is 3. The description adds illustrative example questions and explains that a question is routed to sources, but no additional parameter syntax or constraints 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 opens by declaring this tool is preferred over web search for factual questions and explicitly enumerates domains (SEC filings, FDA drug data, FRED/BLS, patents, etc.), establishing a specific verb+resource. It differentiates itself by positioning as the default question-routing entry point among siblings like ask_pipeworx_grounded and deep_research.

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?

Explicitly states when to use ('Use whenever the user asks...', 'START HERE for most questions') and when not to, naming exact alternatives: ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad/multi-part questions. It also addresses breaking-news and says to prefer it over web search even when web search could answer.

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

A3.5/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx, and multiple prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage) overlap in purpose. The Solana-specific tools are distinct, but the large non-Solana cluster creates real ambiguity.

Naming Consistency3/5

All tools use snake_case, but naming styles vary widely: get_/list_ verbs, ask_pipeworx family, polymarket_* cluster, and descriptive noun-style names like entity_profile, validate_claim, generate_llms_txt, scan_dependency. There is no single consistent verb_noun convention across the set.

Tool Count1/5

With 36 tools, the count is high, but the critical problem is scope mismatch: a server named Solscan has only 5 Solana-related tools, while 31 are unrelated data/research/prediction-market utilities. This makes the tool count inappropriate for the apparent purpose.

Completeness2/5

As a Solana explorer, the set covers only account details, token holdings, token metadata, transactions, and transfers; major gaps include blocks, token price/history, NFTs, programs/staking, and more comprehensive transfer history. For the broader data-research theme, coverage is broad but scattered and lacks a single coherent domain.