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stackexchange

by io.github.pipeworx-io

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. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: it routes to one of 5,798 tools, fills arguments automatically, and returns a structured answer with stable pipeworx:// citation URIs. It does not discuss failure modes or routing errors, but the disclosed behavior is sufficient for a safe read-only invocation.

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

Conciseness3/5

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

The description is front-loaded with the most important guidance and follows a logical structure: preference, examples, then alternatives. However, it is wordy and repeats the same 'prefer over web search / start here' point several times, and the final sentence becomes dense and slightly garbled. It could be tightened without losing meaning.

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 natural-language router tool with no output schema, the description covers what questions it accepts, what it does internally, what it returns (structured answer with citation URIs), and when to use related tools instead. It does not describe the exact response shape or error behavior, but the core invocation context is complete and actionable.

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 input schema has 100% coverage: it documents the `question` parameter, all aliases (q, text, input, query, prompt), and provides examples. The description reinforces that the input is a natural-language factual question and supplies example phrasings, but it adds no parameter-level detail beyond what the schema already provides. Baseline 3 is appropriate here.

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 identifies the tool as a router for factual questions about current or historical data, returning structured answers with citations. It lists specific domains (SEC filings, FDA drug data, FRED/BLS, patents, weather, clinical trials, etc.) and gives concrete example queries. It also distinguishes itself from web search and sibling tools such as 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?

The description explicitly says to prefer this tool over web search for factual/data questions, provides trigger phrases like 'what is', 'look up', 'find', 'get the latest', and gives multiple examples. It also states when not to use it ('use web only when a question is not about facts or data') and names alternatives with conditions: ask_pipeworx_grounded for source verification, bet_research for multi-step math, and deep_research for broad multi-part questions.

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

A3.6/5.0
Disambiguation2/5

The StackExchange tools are distinct, but the dominating data-lookup cluster is highly ambiguous: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), ask_pipeworx_grounded, deep_research, and validate_claim all route into the same underlying tool catalog. The polymorpharket tools also overlap heavily, making selection between bet_research, polymarket_edges, polymarket_arbitrage, and fill-risk checks genuinely hard.

Naming Consistency2/5

The names are all snake_case but otherwise follow no consistent pattern: bare verbs (remember, forget, subscribe), prefixed names (pipeworx_feedback, stack_get_user), composite domain names (ask_pipeworx, generate_llms_txt), and generic verbs (resolve_entity, validate_claim, search_within). The StackExchange subset itself is split between stack_get_user/stack_tags and search_questions/get_answers.

Tool Count2/5

36 tools is already in the 'too many' range for one server, and the mismatch with the server name is severe: only 5 of 36 tools relate to StackExchange. The rest form a broad Pipeworx/prediction-market data platform that would itself be oversized for a focused purpose.

Completeness2/5

For a StackExchange-focused server, the surface has core read operations but lacks question-detail-by-ID, comments, related questions, or any write/community actions, and the 31 unrelated tools do not fill that gap. For the broader apparent Pipeworx platform coverage is broad, but the set has no single coherent domain against which completeness can be meaningfully judged.

Resources