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What Can I Ask Pipeworx?

suggest_questions
Read-onlyIdempotent

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass topic (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional focus area: finance | pharma | economics | real-estate | betting | weather | government | science | news. Omit for a cross-category spread.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds value beyond that by specifying the output structure (category-bucketed example questions, exact tool + argument shape) and the two calling modes (no args vs. with topic), without contradicting the 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 a dense paragraph, but every sentence earns its place: trigger phrases, output content, calling modes, and usage context. It could be improved by breaking into bullets for readability, but it is concise and free of filler.

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 simple tool with one optional parameter and no output schema, the description is remarkably complete. It explains the output format (categories, example questions, tool/argument shape), how to call with or without `topic`, and when to use it first, making it fully self-contained for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers the `topic` parameter with 100% description coverage (explicit list of allowed values). The description augments this with concrete examples ('finance', 'pharma', 'betting') and explains the behavioral difference between omitting and providing the parameter, which goes beyond the schema.

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 the 'onboarding entry point' for discovering what Pipeworx can answer, and specifies it returns category-bucketed example questions with the exact tool + argument shape. This verb+resource+scope clearly distinguishes it from sibling tools like ask_pipeworx (for actual questions) and discover_tools (for tool discovery).

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 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools', which provides clear when-to-use guidance and mentions alternatives. However, it does not explicitly state when NOT to use it, so it stops short of full exclusion guidance.

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

A3.7/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx_beta is currently identical to ask_pipeworx, and find_related with syn/rhy options duplicates find_synonyms and find_rhymes. The six Polymarket tools and four entity-research tools also have fuzzy boundaries, so agents will struggle to reliably pick the right one.

Naming Consistency2/5

Conventions are mixed: most tools follow verb_noun (ask_, find_, compare_, validate_) but several are bare nouns or noun phrases (entity_profile, recent_alertes, recent_changes) and others are bare verbs (remember, forget, subscribe, unsubscribe). The server name 'words' matches only five of 36 tools, adding further confusion about what to expect here.

Tool Count2/5

36 tools is well into the heavy range, and the set bundles word lookups, a universal data router, six Polymarket tools, memory, subscriptions, and meta-utilities under one server. Many of these would be better split into dedicated, purpose-scoped servers.

Completeness4/5

For the dominant data-research and prediction-market scope, the surface is strong: grounded lookups, deep reseach, entity profiles, compareions, change feeds, claim verification, edge scanners, fill-risk checks, subscriptions, and memory are all covered. Minor gaps exist: taking 'words' literally there is no defintion or spelling tool, and there is no generic open-web search, but as a data-research toolkit it is quite complete.