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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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false. The description adds that it returns 'category-bucketed example questions' and uses the 'live catalog', which are useful behavioral details beyond 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 detailed but well-structured: it starts with common questions, then explains behavior, and ends with a usage recommendation. While slightly long, it avoids redundancy and is front-loaded with purpose.

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?

Given no output schema, the description adequately explains the return format (categories, example questions, tool shapes) and the parameter behavior. It also provides context about usage order relative to sibling tools, making it fully informative 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 describes the optional 'topic' parameter with a list of values (e.g., finance, pharma). The description adds context that omitting returns a full spread and that the values focus the results, which enhances understanding 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 states this is the onboarding entry point for new agents, answering queries like 'What can I ask?' and explicitly distinguishes it from sibling tools by explaining its role as a discovery tool.

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?

It explicitly recommends using this tool 'FIRST when you do not yet know what Pipeworx can do' and mentions learning to call meta-tools, but could more explicitly state when not to use it (e.g., if you already know what to ask).

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 heavily overlapping purposes (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; multiple polymarket_* scanners), and the mix of unrelated domains makes it hard to tell which tool is canonical for a task. The few geographic tools are distinct, but they are buried among dozens of non-geographic tools.

Naming Consistency2/5

Naming is a mix of verb_noun (search_geonames, resolve_entity), proper-noun prefixes (pipeworx_*, polymarket_*), and descriptive phrases (ask_pipeworx, bet_research, scan_competitor_ai_presence). No consistent pattern or verb style across the set.

Tool Count2/5

35 tools is far more than a Geonames-focused server needs, and most are unrelated to geospatial data. The count would be borderline for a general data platform, but it is excessive and unfocused for the stated server name.

Completeness1/5

The geographic surface is severely incomplete: only four tools (search_geonames, get_nearby, find_postal_codes, get_timezone) cover a tiny sliver of typical Geonames functionality like reverse geocoding, elevation, or distance calculations. The many non-geographic tools do not compensate for the missing core domain coverage.