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Worldbank Poverty

by io.github.pipeworx-io

List Reference

list_reference
Read-onlyIdempotent

Reference / metadata for the PIP dataset. table="versions" lists available data releases & PPP rounds; table="aux_list" lists all auxiliary tables; any other value (e.g. "countries", "regions", "poverty_lines", "indicators", "dictionary") returns that auxiliary table. Use to look up valid country codes, region mappings, or supported indicators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNo"versions", "aux_list", or an auxiliary table name like "countries" | "regions" | "poverty_lines" | "indicators" | "dictionary". Default "versions".

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and no destructiveness. The description adds behavioral context such as listing specific table behaviors and that it returns metadata, which complements the annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences clearly state purpose and usage. No unnecessary words, front-loaded with the main action.

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 only one parameter and no output schema, the description fully explains all possible values and their intended use. It leaves no ambiguity for the agent.

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 description coverage is 100% and already describes the parameter. The description further clarifies what each table value returns (e.g., 'versions' lists releases, 'aux_list' lists auxiliary tables), adding value beyond the 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?

Clearly states the tool returns reference/metadata for the PIP dataset. It specifies the verb 'list' and the resource, and distinguishes between different table options like 'versions', 'aux_list', and other auxiliary tables.

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 states when to use: 'Use to look up valid country codes, region mappings, or supported indicators.' This provides clear context and implies when not to use alternative tools.

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