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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

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only/open-world/idempotent, and the description adds operational detail: it routes to sub-tools, fills arguments, returns structured answers with pipeworx:// citation URIs, and is 'one fast call'. This goes beyond the annotation profile. It does not mention rate limits or failure behavior, but the core behavioral contract is disclosed.

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 sectioned: core directive, behavior, trigger phrases, examples, and escalation path. A few items are redundant (the domain list and trigger phrases overlap), but every major decision an agent needs is present.

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, no-output-schema router, the description covers input (natural-language question), output (structured answer with citation URIs), and escalation rules. It also handles the breaking-news edge case. It does not describe what happens when no source matches, but that is a minor gap for a default entry-point tool.

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 coverage is 100%; the `question` parameter already documents natural-language input and its aliases. The description reinforces with examples but adds no semantic detail beyond the schema, so a 3 baseline 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 the question to the right one of 5,724 tools across 1497 verified sources') and a clear resource (authoritative structured data with citations). It differentiates ask_pipeworx from siblings by naming ask_pipeworx_grounded and deep_research as fallback alternatives. The core purpose — factual query routing and answering — is unambiguous.

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 instructs 'PREFER OVER WEB SEARCH' and 'START HERE for most questions', with trigger phrases like 'what is', 'look up', 'find'. It also states when not to use: 'Step up only when needed... for a hallucination-resistant single answer... use ask_pipeworx_grounded; for a broad/multi-part question... use deep_research' — supplying named alternatives and conditions.

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 clusters of near-duplicates force careful reading: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded overlap heavily; the five polymarket tools share edge-detection and arbitrage territory; and ai_visibility_check vs scan_competitor_ai_presence are easy to confuse. discover_tools, suggest_questions, and pipeworx_trending also compete as discovery/onboarding entry points.

Naming Consistency3/5

All names are lowercase snake_case, so there is surface consistency, but the structural pattern is mixed: verb_noun (list_feeds, read_feed, resolve_entity), noun_verb (ai_visibility_check), noun_noun (entity_profile, polymarket_fill_risk), and bare verbs (remember, forget). Prefixes like ask_pipeworx and polymarket create local order, but no server-wide naming convention holds.

Tool Count2/5

34 tools for a server named 'Gaming Feeds' is heavily over-scoped; only list_feeds, read_feed, and fetch_feed actually serve that purpose. The remaining ~25 tools constitute an unrelated Pipeworx data platform covering queries, prediction markets, memory, subscriptions, and feedback, making the count feel like a bundled mega-server rather than a focused toolset.

Completeness3/5

For the nominal gaming-feed domain, list/read/fetch plus keyword filtering covers basic consumption, but there is no cross-feed search, feed management, or feed-specific subscription support (subscribe only handles SEC, Polymarket, and FRED streams). The broader data/research surface is comprehensive internally, but that completeness belongs to a different server's purpose.