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catfacts

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

A4.3/5.0
Behavior5/5

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

Annotations already indicate a read-only, idempotent, non-destructive tool, and the description adds substantial behavioral context beyond that: candidate routing improvements are enabled live only when one is under test, no candidate is currently active, the tool currently matches ask_pipeworx exactly, and it falls back to nothing because it is a full working router. This is excellent disclosure of the experimental nature and current operational state, with no contradiction of annotations.

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 longer than average but every sentence contributes: beta status, identity with ask_pipeworx, live-candidate behavior, current state, usage direction, comparison purpose, and the 'full working router' reassurance. It is front-loaded with the most important distinction and is structured logically, though it could be trimmed slightly 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 beta alias tool with no output schema, the description covers the critical context: what it is, that it is currently identical to ask_pipeworx, how to use it, and what experimental behavior means. It intentionally defers response-shape detail to ask_pipeworx rather than restating it; this is acceptable given the sibling relationship, but it leaves an agent without direct access to ask_pipeworx's description slightly under-informed.

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 already describes the parameters with 100% coverage, including aliases for the required question field. The description adds that the tool has the 'same arguments' as ask_pipeworx, which is mildly helpful, but it does not enrich the meaning of individual parameters beyond what the schema already provides, so the schema-carrying baseline of 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?

The description is specific and immediate: it identifies the tool as a beta version of ask_pipeworx, an identical universal router over 5,798 tools with the same arguments and response shape. It clearly distinguishes this tool from the stable ask_pipeworx by labeling it the experimental edge with candidate routing improvements, so an agent can tell them apart.

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?

"Use it exactly like ask_pipeworx when you want the newest routing" gives an explicit usage condition, and the description explains that results are compared against the stable router to decide merges. It lacks an explicit when-not-to-use statement, such as 'prefer ask_pipeworx for stable production use,' but the context is clear enough.

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

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical in routing, differing only in response mode; bet_research and polymarket_edges both surface betting opportunities. Even with detailed descriptions, an agent could easily select the wrong one for a given task.

Naming Consistency2/5

Tool names are all snake_case, but the pattern is inconsistent: some are verb_noun (get_fact, list_breeds, validate_claim), some are noun/adjective compounds (entity_profile, deep_research, bet_research), and several use a pipeworx_ prefix. There is no consistent verb style or object-first convention.

Tool Count2/5

34 tools is over the 25-tool threshold for a server whose name suggests a narrow cat-facts focus. Only 3 tools relate to cat facts; the rest form a sprawling data platform, creating a severe scope mismatch that makes the count feel excessive and unfocused.

Completeness3/5

For the cat-facts domain, the set covers the essentials: single fact, multiple facts, and breed listing. However, the overall tool surface is a mix of unrelated capabilities (data lookups, memory, subscriptions, prediction markets) that don't form a coherent domain, leaving the cat-facts portion sparse and the broader set without clear lifecycle coverage.