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Glama

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 5,798 tools across 1517 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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed6 schema fields changed
    • addedInput schema / properties / input
      Added value: +{
      +  "description": "Alias for question.",
      +  "type": "string"
      +}
    • addedInput schema / properties / prompt
      Added value: +{
      +  "description": "Alias for question.",
      +  "type": "string"
      +}
    • addedInput schema / properties / q
      Added value: +{
      +  "description": "Alias for question.",
      +  "type": "string"
      +}
    • addedInput schema / properties / query
      Added value: +{
      +  "description": "Alias for question.",
      +  "type": "string"
      +}
    • changedInput schema / properties / question / description
      Previous value: -"Your question or request in natural language"New value: +"Your question or request in natural language. Accepts query, q, prompt, text, input as aliases."
    • addedInput schema / properties / text
      Added value: +{
      +  "description": "Alias for question.",
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "question": "What was Apple's revenue in 2024?"
      +  },
      +  {
      +    "question": "Any recent SEC filings for $NVDA?"
      +  },
      +  {
      +    "question": "Current price of bitcoin"
      +  }
      +]
  3. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds meaningful extra behavior: it routes to one of 5,798 tools, fills arguments automatically, and returns structured answers with stable pipeworx:// citation URIs. This goes well beyond the annotations and no contradiction exists.

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 well structured, front-loading the most important guidance and grouping supporting details logically. The many examples earn their place, though 'START HERE for most questions' is somewhat redundant with the opening preference statement.

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?

For a complex routing tool with no output schema, this description is unusually complete: it explains scope, mechanism, output form, citation scheme, when to prefer it, and which alternative to use for broader questions. Nothing critical is missing for an agent to 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?

The schema covers all parameters at 100%, so the baseline is 3. The description adds value by emphasizing that the parameter is a natural-language question and by providing concrete example queries, which helps an agent format the input correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's role: it routes a natural-language factual question to one of many verified sources and returns a structured, cited answer. It distinguishes itself from web search and deep_research, though it never differentiates from the closely named ask_pipeworx_beta and ask_pipeworx_grounded siblings.

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?

Usage guidance is explicit and rich: prefer over web search, use for a broad list of factual topics, trigger phrases are given, and concrete examples show when to invoke it. It also names an alternative, deep_research, for broad/multi-part questions and clarifies that breaking news is 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

A3.7/5.0
Disambiguation2/5

The set has several overlapping tool clusters. ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, ai_visibility_check and scan_competitor_ai_presence overlap heavily, and polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and polymarket_fill_risk all target opportunity-finding/fill-checking on prediction markets. While individual descriptions are detailed, an agent could easily pick the wrong tool among these near-duplicates.

Naming Consistency2/5

Naming is inconsistent across the surface. The monday_* and polymarket_* prefixes are consistent within their subgroups, and ask_pipeworx_* forms a family, but the rest mix verb_phrase (validate_claim, compare_entities, discover_tools), noun_phrase (entity_profile, recent_changes, suggest_questions), and bare verbs (remember, forget, recall) with no unifying pattern. This makes it hard to predict tool names.

Tool Count2/5

At 36 tools, the surface is overloaded. The Monday.com integration alone only needs 5 tools, and the remaining 31 are a sprawling research/meta-toolkit. Many of these could be consolidated (e.g., ask_pipeworx and ask_pipeworx_beta, or the several polymarket scanners), so the count feels inflated beyond what the server's core purpose requires.

Completeness3/5

The data-research and monitoring side is thorough, covering querying, grounding, comparison, profiling, entity resolution, subscriptions, memory, and feedback. However, the Monday.com integration is incomplete: it offers create/list/get/search for items but no update or delete operations, and no board creation or modification. This leaves the Monday workflow with dead ends.