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Ask Pipeworx Beta

ask_pipeworx_beta
Read-onlyIdempotent

Beta version of ask_pipeworx: identical universal router (same 5,743 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 substantial behavioral context beyond that: it is experimental, candidate routing improvements are enabled live when under test, currently no candidate is active so it matches ask_pipeworx exactly, and results are compared against the stable router to decide merges. This is exactly the kind of nuance an agent needs to interpret outputs and choose confidently.

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 but purposeful, with each sentence contributing a distinct fact: beta status, identical behavior, current no-candidate state, usage direction, and fallback clarification. It is front-loaded with the beta relationship, although the parenthetical detail about the retired candidate and the date is slightly extraneous. Overall it earns its length.

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 tool with a single natural-language parameter and no output schema, the description provides the essential context: it is a full working router, identical to ask_pipeworx, and currently in a known experimental state. It references the response shape as identical to ask_pipeworx but does not describe what that shape is, which is a minor gap; however, an agent can consult the sibling tool's documentation. This is complete enough for correct invocation.

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 schema provides 100% description coverage for all six parameters, including the required 'question' and its five aliases, so the structured data already carries the parameter semantics. The description only adds that the tool takes 'the same arguments' as ask_pipeworx, which is a helpful but not necessary restatement. With such high schema coverage, the 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?

The description clearly states what the tool is: a 'universal router' over 'the same 5,743 tools' with 'the same arguments and response shape' as ask_pipeworx. It also explicitly differentiates itself from the sibling ask_pipeworx by being the beta version with candidate routing improvements. This gives a specific verb, resource, and scope.

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 advises to 'Use it exactly like ask_pipeworx when you want the newest routing,' naming the alternative and the condition that selects it. It also clarifies that this is a full working router that 'falls back to nothing,' so an agent won't mistake it for a stub. It does not exhaustively contrast with ask_pipeworx_grounded, but the primary routing decision is well covered.

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

A3.9/5.0
Disambiguation2/5

Several tool clusters are nearly indistinguishable in purpose: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same underlying catalog, and the six polymarket tools heavily overlap in surfacing prediction-market edge. Even with detailed descriptions, an agent could easily misselect between bet_research and polymarket_edges or between discover_tools and suggest_questions.

Naming Consistency3/5

Most names use lowercase snake_case, but the pattern is mixed: some are verb_noun (compare_entities, resolve_entity), some are bare verbs (remember, forget, recall), and some are compound noun phrases (polymarket_edges, pipeworx_trending). ask_pipeworx also breaks the separator convention compared to ask_pipeworx_beta and ask_pipeworx_grounded.

Tool Count2/5

With 32 tools, this exceeds the 25+ threshold for 'too many' and feels like a platform bundle rather than a focused server. It spans data querying, prediction markets, memory, subscriptions, feedback, AI visibility, dependency scanning, and llms.txt generation, which is far more surface area than one coherent server should present.

Completeness4/5

For the core data-research and prediction-market domains, coverage is strong: query, grounded verification, deep research, entity resolution, comparisons, change feeds, arbitrage, fill-risk, subscriptions, and memory are all present with no major dead ends. The gaps are mostly the single-purpose oddballs (could_have_been_email_analyze, generate_llms_txt, scan_dependency) that don't connect to the rest of the surface.