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Ask Pipeworx Beta

ask_pipeworx_beta
Read-onlyIdempotent

Beta version of ask_pipeworx: identical universal router (same 5,798 tools, same arguments, same response shape) with candidate routing improvements enabled live whenever one is under test. No candidate is active right now (the last was retired on outcome evidence 2026-07-26), so this currently matches ask_pipeworx exactly. Use it exactly like ask_pipeworx when you want the newest routing; results are compared against the stable router to decide what merges. Falls back to nothing — this IS a full working router, just the experimental edge.

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. Added

TDQS

A4.5/5.0
Behavior5/5

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

The annotations already mark this read-only/open-world/idempotent, and the description adds valuable behavioral context: live candidate routing improvements, current inactive candidate with a retirement date, exact equivalence to ask_pipeworx today, and a clear statement that it does not fall back to anything yet is a full working router. This goes well beyond the structured hints.

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

Conciseness5/5

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

Four sentences with no wasted phrases; each sentence adds distinct information: identity/differences, current status, usage guidance, and reassurance about fallback behavior. The most decision-relevant information (beta, same interface) is front-loaded.

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 single-required-parameter router with no output schema, the description is complete: it specifies the input pattern, current behavior, relationship to the stable sibling, response-shape equivalence, and operational caveats. An agent has everything needed to invoke it 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?

Schema coverage is 100%: all six properties are described, with q/text/input/query/prompt all documented as aliases for question. The description adds nothing about parameters beyond noting the same arguments as ask_pipeworx, so the schema carries the load and a baseline 3 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?

States a specific resource (universal question-answering router), the action (ask), and the beta-vs-stable distinction relative to ask_pipeworx. It names the sibling (ask_pipeworx) and clarifies that this variant is the experimental routing edge, so an agent can distinguish it without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use it like ask_pipeworx when the newest routing is desired, and mentions results are compared against the stable router. It gives clear context and names the alternative, though it never spells out an explicit 'do not use when...' exclusion, making it a strong 4 rather than a 5.

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

A4.1/5.0
Disambiguation5/5

Each tool has a detailed description clarifying its precise purpose, and even closely related tools (e.g., ask_pipeworx vs ask_pipeworx_grounded) are clearly differentiated by behavior and use case. No two tools appear to serve the same function.

Naming Consistency3/5

All names use snake_case, but the structural pattern is inconsistent: many follow verb_noun (compare_entities, resolve_entity), while others are noun-based (entity_profile, polymarket_arbitrage) or single verbs (subscribe, remember). This mix reduces predictability.

Tool Count3/5

With 32 tools, the server is quite large for an MCP server. While many tools are justified by the broad domain coverage, the high number can overwhelm agents and increase cognitive load, making it feel somewhat bloated.

Completeness4/5

The tool set covers a wide range of domains (company data, prediction markets, news, memory, subscriptions, etc.), and the generic ask_pipeworx and deep_research tools gateways to thousands of data sources, effectively filling gaps. However, some areas lack dedicated tools (e.g., weather, real estate) beyond the generic query.