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Macro Snapshot

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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds context (category-bucketed examples, tool+argument shape, live catalog) without contradiction, and provides usage behavior (optional topic narrowing).

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 example queries and structured logically, but is somewhat lengthy. 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 the tool's role as an onboarding guide with no output schema, the description fully explains what it returns, how to call it, topic options, and when to use it relative to other tools. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with topic description listing options. The description repeats these options in natural language and adds the nuance that omitting topic yields cross-category spread, but this is marginal added value.

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 returns category-bucketed example questions with tool suggestions, distinguishing it from siblings like ask_pipeworx and compare_entities by positioning it as the onboarding entry point.

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 'Use this FIRST' when the agent doesn't know what Pipeworx can do, and explains how to call it with or without a topic, as well as mentioning related meta-tools for further action.

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

A4.1/5.0
Disambiguation2/5

Several tools occupy heavily overlapping space: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same router, with the beta version explicitly noted as currently identical to the stable one. The six polymarket_* tools plus bet_research and macro_snapshot/indicator further blur boundaries, so an agent could easily route a query to the wrong entry point despite the detailed descriptions.

Naming Consistency4/5

Names are consistently snake_case and mostly follow a verb_first or domain_prefix pattern (ask_pipeworx, resolve_entity, validate_claim, polymarket_edges). Minor deviations like entity_profile, indicator, macro_snapshot, and recent_alerts use noun phrases, but the style is still predictable and readable.

Tool Count2/5

At 33 tools, the surface is heavy and exceeds the 25+ threshold for 'too many'. While the server covers many domains, several tools are near-duplicates or conveniences (ask_pipeworx_beta, scan_competitor_ai_presence, indicator) that could be consolidated.

Completeness5/5

For its apparent scope—structured data Q&A, grounded research, entity comparison, prediction-market analysis, subscriptions, and memory—the tool set covers the full lifecycle: query, ground, verify, research, compare, monitor, subscribe, alert, and manage state. There are no obvious dead ends; even supporting workflows like discover_tools and suggest_questions are provided.

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