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by io.github.pipeworx-io

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
Behavior5/5

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

Adds rich behavioral context beyond annotations: explains that it returns category-bucketed example questions with tool+argument shapes, can be called with no arguments or a topic, and draws from a live catalog. No contradiction with 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 front-loaded with purpose and packs useful information, but is slightly verbose with multiple phrasings. Every sentence adds value, so it remains efficient.

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 the single optional parameter, full schema coverage, and rich annotations, the description fully covers the tool's behavior, output, and usage context, leaving no gaps.

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 value by listing specific topic values and explaining the effect of omitting or passing a topic, which exceeds the schema's description.

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 defines the tool as an onboarding entry point that generates example questions about Pipeworx's capabilities, listing common user phrasings and distinguishing it from siblings 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 Guidelines4/5

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

Explicitly states 'Use this FIRST when you do not yet know what Pipeworx can do for you', providing clear context for when to use. Does not explicitly list exclusions or alternatives, but the guidance is strong.

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 set mixes Salesforce CRUD tools with a large Pipeworx research and prediction-market platform, and several tools overlap heavily: ask_pipeworx vs ask_pipeworx_beta are functionally identical, grounded/validate_claim/deep_research cover similar lookup/verification territory, and the six polymarket/bet tools share edge-finding purposes with only subtle distinctions. An agent would need to read long descriptions carefully to pick the right one, so misselection risk is high.

Naming Consistency3/5

Salesforce tools follow a clear sf_verb_noun pattern, and the Pipeworx tools mostly use lowercase snake_case phrase names, but the conventions diverge: ask_pipeworx has no underscore, deep_research/entity_profile are noun phrases rather than verb-first, and the sf_* prefix is a separate naming family. It is still readable, but it is not a single predictable pattern.

Tool Count2/5

39 tools is well past the heavy threshold, and most belong to a broad data/research platform rather than the Salesforce scope implied by the server name; only 8 tools are actually Salesforce CRUD/query operations. The count feels bloated for a coherent assistant, even if individual features are useful.

Completeness4/5

The Salesforce subset is complete: create/get/update/delete/query/search/describe/list-object cover the record lifecycle with no dead ends. The broader Pipeworx ecosystem also has strong coverage, including routing, grounded verification, research, entity resolution, memory, and subscriptions, with only minor gaps such as no direct citation-fetch tool and no Salesforce upsert/bulk operations.

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