Skip to main content
Glama

Ask Pipeworx Beta

ask_pipeworx_beta
Read-onlyIdempotent

Beta version of ask_pipeworx: identical universal router (same 5,718 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.

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, but the description adds meaningful context: it is a live experimental edge, candidates can be enabled at any time, it currently matches ask_pipeworx exactly, and it 'falls back to nothing' as a full working router rather than a stub. This goes beyond the structured hints and gives a clear behavioral model.

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 dense and front-loaded with the tool's identity and relationship to ask_pipeworx. Each sentence adds useful operational information, though phrases like 'identical universal router' alongside 'same 5,718 tools, same arguments, same response shape' are slightly redundant. Overall it is appropriately sized for a beta tool with an important distinction.

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 router tool with no output schema, the description covers the essential context: what it routes to, why it is experimental, current status, how to use it, and that it is not a fallback. The 'same response shape' reference provides return-value context by analogy to ask_pipeworx. It could be improved by explicitly describing the output shape, but the current coverage is strong.

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%, with each parameter described as an alias for 'question' and a clear natural-language description on the question field itself. The description says 'same arguments' but adds no semantic detail beyond what the schema already provides. Baseline 3 is appropriate because the schema handles parameter meaning fully.

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 beta version of ask_pipeworx, a universal router that dispatches to 5,718 tools. It explicitly states it uses the same arguments and response shape, and differentiates itself from the stable sibling by its experimental routing edge. An agent can understand what this tool does and how it differs from ask_pipeworx without opening the schema.

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?

The description explicitly says to use it like ask_pipeworx 'when you want the newest routing' and notes that results are compared against the stable router. It also clarifies that no candidate is active right now, so behavior currently matches the stable tool. However, it lacks an explicit when-not-to-use statement, though the contrast with the stable router implies the stable alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation3/5

Most tools have clearly distinct roles, and the extensive descriptions help differentiate intent, but the ask_pipeworx family—especially ask_pipeworx_beta, which is currently identical to ask_pipeworx—creates real ambiguity. Overlapping entry points like ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim could also cause misselection without careful reading.

Naming Consistency4/5

All 34 tools use consistent snake_case, and clear verb-led or noun-prefixed patterns emerge across families like ask_pipeworx*, polymarket_*, and remember/recall/forget. Minor deviations such as ai_visibility_check and recent_changes being noun phrases rather than verb_noun constructions prevent a perfect score.

Tool Count2/5

34 tools is well above the 25-tool threshold for over-scoping, making the set heavy for an agent to navigate. While the server spans many domains, several tools like generate_llms_txt, scan_dependency, and ai_visibility_check feel tangential to the core news/research purpose and would be better split into separate servers.

Completeness4/5

The core news/research domain is well covered: lookup, grounded verification, deep multi-source research, entity profiles, comparisons, subscriptions, and alert feeds are all present with no obvious dead ends. Minor gaps exist—such as no direct full-text article retrieval or a dedicated free-text news search beyond latest_news filters—but agents can work around them.