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Ask Pipeworx Beta

ask_pipeworx_beta
Read-onlyIdempotent

Beta version of ask_pipeworx: identical universal router (same 5,908 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

A4.4/5.0
Behavior5/5

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

Beyond the annotations, it discloses that this is an experimental edge, that candidate routing improvements are enabled live only while under test, that the last candidate was retired on a specific date, and that it currently matches ask_pipeworx exactly. It also explicitly says it falls back to nothing and is a full working router.

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 front-loaded with the tool's identity and experimental nature, then gives current state and usage context. It is slightly longer than strictly necessary, but each sentence contributes useful caveats about routing behavior.

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 beta router with no output schema, it conveys current behavior, relationship to the stable router, argument compatibility, experimental status, and failure mode. An agent can decide when to call it and what to expect, especially because the response shape is defined by parity with ask_pipeworx.

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 description coverage is 100% and each parameter is already described as an alias for question. The description adds only the claim that arguments match ask_pipeworx, but provides no additional syntax, format, or semantic detail beyond what the schema already gives.

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?

Opening sentence states it is the beta version of ask_pipeworx with an identical universal router across 5,798 tools, same arguments, and same response shape, plus candidate routing improvements. This makes the action and resource clear and distinguishes it from ask_pipeworx and ask_pipeworx_grounded.

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?

It explicitly says to use it like ask_pipeworx when wanting the newest routing, and clarifies that no candidate is currently active so behavior matches stable. It does not explicitly state a 'do not use' condition for cases requiring guaranteed stable behavior, but the experimental framing makes that largely inferable.

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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