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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

A4.8/5.0
Behavior5/5

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

Annotations provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds value by detailing return content (category-bucketed example questions with exact tool+argument shapes) and that it draws from live catalog. 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?

Description is fairly long but efficiently packs key information. Uses examples and brief categorization. Could be slightly more concise but remains readable.

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 provides comprehensive context: use case, return structure, topic examples, and relation to other tools. Complete.

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 covers the single optional parameter with description. Description adds context: examples of topic values (finance, pharma, etc.) and behavior when omitted (full spread). Slight value-add over 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 the tool is for onboarding, answering 'what can I ask?' and returns category-bucketed example questions with tool+argument shapes. It distinguishes from sibling tools like ask_pipeworx, discover_tools, etc.

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 instructs to 'Use this FIRST' when unsure of capabilities, and says to call with no arguments for full spread or pass a topic. Mentions alternatives like ask_pipeworx, entity_profile, compare_entities.

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

Multiple tools have overlapping purposes, especially the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research) which all serve to query data but with subtle differences. An agent would struggle to distinguish which to use without deep understanding of their nuances.

Naming Consistency3/5

Most tool names follow a verb_noun or noun_noun pattern in snake_case, but there are exceptions like 'forget', 'recall', 'remember' which are single verbs, and names like 'ask_pipeworx' mix verb and proper noun. Overall pattern is discernible but not uniform.

Tool Count2/5

33 tools is high for a server named 'Open Sanctions' which implies a focused domain. The tool set spans sanctions, meta-querying, prediction markets, memory, subscriptions, and more, making it feel bloated and unfocused relative to the server's name.

Completeness2/5

For a sanctions server, only two tools (search_entities, get_entity) directly address the domain, missing obvious operations like update, delete, or list. Many tools are unrelated to sanctions, leaving the core domain incomplete.