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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

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, fully covering the safety and idempotency profile. The description adds the context of being an onboarding entry point and return structure, but no new behavioral traits beyond what annotations imply.

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 with useful information in a single paragraph, using dashes to list categories. It is front-loaded with purpose and usage. While every sentence is valuable, it could be slightly more concise by separating the listing into a clearer structure.

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?

Given one optional parameter, no required fields, and no output schema, the description covers the tool's purpose, usage context, parameter guidance, and expected return content (category-bucketed examples). It is nearly complete, but lacks explicit description of the return JSON structure, which would be helpful since there is no output schema.

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?

Schema coverage is 100%, so baseline is 3. The description adds significant meaning by explaining the $topic parameter's purpose (focus on a category) and listing the exact focus areas (finance, pharma, etc.), which goes beyond the schema's minimal description. This helps the agent use the parameter more effectively.

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 it's the onboarding entry point for a newly connected agent, explaining it returns category-bucketed example questions with specific tool+argument shapes. It also explicitly distinguishes from sibling tools like ask_pipeworx and entity_profile, covering what it does and who it's for.

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 states 'Use this FIRST when you do not yet know what Pipeworx can do for you' and explains the optional $topic argument for focusing. However, it does not provide explicit when-not-to-use guidance or alternatives, though the context is clear.

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 are near-clones: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded differ mainly by mode, and deep_research overlaps with all of them. The five polymarket_* tools plus bet_research also blur together, and discover_tools vs suggest_questions both serve a 'what can I do' purpose.

Naming Consistency3/5

All names are readable snake_case, but the convention is mixed: verb-first (get_current_standings, validate_claim, scan_dependency), noun-first (polymarket_edges, pipeworx_trending), and bare verbs (remember, forget, subscribe). The F1 tools follow a clean get_* pattern that doesn't extend to the rest of the set.

Tool Count2/5

35 tools is excessive, especially since the server is named 'F1' but only 4 tools relate to F1. The set could be consolidated substantially: three ask_pipeworx variants, multiple overlapping polymarket scanners, and two tool-discovery helpers all add weight without clear scope.

Completeness2/5

The F1 side is thin: no qualifying results, constructor standings, lap data, circuits, or driver search by name. The Pipeworx half is broad, but it belongs to a different domain, leaving the overall surface feeling incomplete for either purpose.