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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.

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds that the tool returns tool+argument shapes from the live catalog, which is useful context beyond annotations. No contradictions.

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 common user phrasings and is detailed, but every sentence contributes value. Slightly longer than necessary but still efficient for the complexity.

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?

No output schema, but the description explains the return format (category-bucketed example questions with tool+argument shapes). For a discovery tool, this is sufficiently complete given the annotations and schema richness.

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

Parameters5/5

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

Schema coverage is 100% and the description elaborates on the topic parameter with concrete examples (finance, pharma) and explains the default behavior when omitted, fully compensating for any lack of schema detail.

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 uses specific verbs ('returns category-bucketed example questions') and clearly states the resource (Pipeworx capabilities). It distinguishes from siblings like ask_pipeworx and discover_tools by positioning itself as the onboarding entry point.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this FIRST when you do not yet know what Pipeworx can do' and provides alternative queries. It also explains how to call meta-tools, giving clear when-to-use 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

The four card tools are distinct, but the majority of the server is a Pipeworx/prediction-market platform with heavily overlapping entry points: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools all serve similar query/discovery purposes, and ask_pipeworx_beta is explicitly an identical twin of ask_pipeworx. The six Polymarket tools and the ai_visibility/scan_competitor pair also have fuzzy boundaries that would make tool selection error-prone.

Naming Consistency2/5

All names are snake_case, but the pattern is highly inconsistent: some are verb_noun (get_card, search_cards, resolve_entity), some are bare verbs (remember, forget), some are noun-first (polymarket_edges, entity_profile, bet_research), and some are adjective_noun (recent_alerts, recent_changes). The ask_pipeworx variants share a name but differ only by suffix, which is not a clear action-oriented pattern.

Tool Count2/5

35 tools is squarely in the 'too many' territory, and the bloat is worse because the server is named Tcgdex while only 4 of 35 tools actually relate to trading cards. The remaining 31 tools form a sprawling multi-domain platform that mixes data queries, prediction markets, memory, subscriptions, AI visibility checks, and one-off utilities like generate_llms_txt and scan_dependency.

Completeness4/5

For the TCGdex card surface, the read-only workflows are covered well: search_cards leads to get_card, and list_sets leads to get_set, with no obvious dead ends. For the broader Pipeworx functionality, the set includes discovery, query, grounding, entity resolution, memory, subscriptions, and feedback, so the main workflows are supported—though the overall scope is sprawling rather than focused.