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Worldbank Poverty

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

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds significant behavioral context: it returns 'category-bucketed example questions' with 'exact tool + argument shape' drawn from a 'live catalog', which matches the openWorldHint and explains the dynamic nature. 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?

The description is detailed but efficient, using examples of queries to front-load the purpose. It packs a lot of information (output nature, parameters, usage) into a few sentences without redundancy. Slightly longer than ideal but earns its length.

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?

With no output schema, the description fully explains the return format (category-bucketed examples with tool+argument shapes). It covers all essential aspects: purpose, usage guidance, parameter semantics, and behavioral traits. No gaps remain for a tool of this complexity.

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

Parameters5/5

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

Schema coverage is 100% with a single optional topic parameter. The description adds meaning beyond the schema by specifying that omitting topic gives a 'full spread' while passing a topic 'focuses' on that area, and lists valid topic values (finance, pharma, etc.). This enriches the schema's minimal 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 states the tool as the 'onboarding entry point' for agents, specifically returning category-bucketed example questions with tool+argument shapes. It distinguishes itself from sibling tools like ask_pipeworx and entity_profile by positioning itself as a first-use tool to learn capabilities.

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?

The description explicitly instructs to use this tool 'FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools', and implies that other tools are for subsequent use. This provides clear when-to-use guidance and differentiates from siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Worldbank Poverty toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) which all route to the same data sources. Additionally, the server includes unrelated meta-tools (remember/recall/forget, generate_llms_txt, pipeworx_feedback) that have no clear boundaries with the poverty data tools, and betting tools that seem out of place. The core poverty tools (get_poverty, get_poverty_regional, list_reference) are distinct, but the rest creates significant confusion.

Naming Consistency2/5

Tool names are a mix of styles: some use snake_case (get_poverty, list_reference, suggest_questions), some use camelCase (ask_pipeworx, bet_research, scan_competitor_ai_presence), and others are single words (recall, remember, forget, subscribe). The naming pattern is highly inconsistent, making it hard to predict related tool names.

Tool Count2/5

With 34 tools, this server is heavily overloaded for a 'Worldbank Poverty' server. The majority of tools are unrelated to poverty (Polymarket betting, AI marketing, npm package checks, LLM visibility). The core poverty functionality could be served by 3-5 tools, but instead the server includes dozens of extra tools from a generic data platform, making the count inappropriate for the stated domain.

Completeness4/5

For the poverty data domain, the tool surface is actually quite complete: get_poverty for country-level data, get_poverty_regional for aggregations, and list_reference for metadata. The only minor gap is a lack of a tool for comparing poverty across countries directly, but that is easy to work around by calling get_poverty multiple times. The extra meta-tools do not affect poverty data completeness.

Resources