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xmpuspus

ph-civic-data-mcp

by xmpuspus

Philippine poverty incidence

get_poverty_stats
Read-onlyIdempotent

Retrieve poverty incidence statistics for the Philippines, optionally filtered by region, from the latest PSA data.

Instructions

Poverty incidence from the PSA Full Year Poverty Statistics table.

PSA publishes this once a year, with a lag. As of 2026-09 the latest published year is 2023. The tool discovers the current table live, so a later release shows up without a code change. It also returns the subsistence incidence when PSA publishes both tables for the same year. Examples:

get_poverty_stats() national poverty incidence, latest year get_poverty_stats(region="Bicol") one region, PSA label get_poverty_stats(region="NCR") National Capital Region

On failure: a discovery failure, a missing Incidence dimension, an unparseable year label, or a query failure sets data_status "unavailable" and upstream_error true. A region PSA does not list sets data_status "invalid_request" and validation_error true. A table with no matching incidence measure, or a cell whose values field is not a list, sets data_status "indeterminate" and upstream_error true. A published ".." cell for the region and year sets no error flag and no data_status. Check caveats instead. A subsistence-table failure sets upstream_error true on an otherwise valid poverty figure, but leaves data_status at "success".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionNoPH region (None returns national).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.0
  2. Removedv1.0.4
  3. Addedv1.0.2

TDQS

A4.4/5.0
Behavior5/5

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

The description goes well beyond the readOnly/idempotent annotations by detailing data_status values, upstream_error and validation_error conditions, handling of unpublished '..' cells, and subsistence-table failure behavior. This gives an agent a clear picture of success and failure modes.

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 the core purpose, followed by examples and then failure semantics. It is somewhat lengthy but each section serves a distinct informative purpose, and the organization is logical.

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 existing output schema, the description covers source cadence, data lag, live discovery, examples, and an extensive set of error/status behaviors. It is sufficiently complete for an agent to invoke the tool correctly and interpret unusual results.

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?

The input schema already describes the optional region parameter and its None default. The description adds useful examples with 'Bicol' and 'NCR', and clarifies that an unlisted region leads to an invalid_request status, enriching the parameter semantics 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?

The description clearly states that the tool returns poverty incidence from the PSA Full Year Poverty Statistics table, and the title and examples make the tool's purpose immediately understandable. It is distinct enough from siblings by referencing the specific PSA poverty dataset.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description implies usage when PSA poverty incidence data is needed, and the examples show national and regional calls. However, it does not explicitly compare against sibling tools or state when not to use this tool, so guidance is mainly implicit.

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