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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
Behavior3/5

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

Annotations already cover read-only, idempotent, non-destructive nature. Description adds that it returns category-bucketed examples with tool shapes, but doesn't disclose additional 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?

Description is somewhat lengthy but front-loaded with alternative phrasings and purpose. Every sentence adds value, though it could be slightly more concise.

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 and rich annotations, the description fully explains the return format (category-bucketed questions with tool shapes) and use cases, making it complete for a discovery tool.

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% and the description adds meaning by explaining the topick parameter's purpose and listing example values.

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 is an onboarding entry point that returns example questions with exact tool calls, distinguishing it from sibling tools like ask_pipeworx and discover_tools.

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 to use this first when unsure of Pipeworx's capabilities, and describes optional topic parameter to focus on a specific area.

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

A3.8/5.0
Disambiguation2/5

The legislation-specific tools are distinct, but the server bundles dozens of unrelated Pipeworx/prediction-market/AI-visibility tools, making the set's purpose unclear. Several near-identical pairs exist: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ai_visibility_check overlaps heavily with scan_competitor_ai_presence. An agent would struggle to know which tool is the right entry point.

Naming Consistency2/5

Naming is mixed: snake_case dominates, but camelCase appears in ask_pipeworx, ask_pipeworx_grounded, generate_llms_txt, and pipeworx_feedback. There is also inconsistency in verb style — get_/search_/list_ coexist with bare verbs like remember, recall, forget, and subscribe. The legislation tools themselves follow a clean get_legislation* pattern, but the wider set does not.

Tool Count2/5

35 tools is too many for a server named 'Legislation Uk' where only 4 tools actually relate to UK legislation. The remaining 31 tools appear to belong to a broader data/prediction-market platform, which suggests severe scope creep or a mislabeled assembly. This bloats the surface area and makes the server harder for an agent to navigate.

Completeness4/5

For the stated UK-legislation purpose, the core read-and-search workflow is covered: search_legislation, get_legislation, get_legislation_section, and get_legislation_text together support discovery, metadata, targeted section lookup, and full-text retrieval with version selection. Obvious gaps remain, such as full-text content search and amendment/change history, but agents can complete the primary task of finding and reading legislation. The unrelated tools neither help nor complete this domain.