Skip to main content
Glama
Sign In
andikadevs

pddikti

by andikadevs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Get aggregate statistics

get_statistics
Read-onlyIdempotent

Retrieve national aggregate statistics for Indonesian higher education—student, lecturer, university, or study program counts—as JSON, with no institution ID required.

Instructions

Fetch one national aggregate statistic for Indonesian higher education as JSON. Needs no id; use it for country-wide counts, not for a single institution. Statistic metric. "mhs-count" — Get total student count; "mhs-count-active" — Get active student count; "mhs-count-gender" — Get student count by gender; "mhs-count-bidang-ilmu" — Get student count by field; "mhs-count-status" — Get student count by status; "mhs-count-jenjang" — Get student count by degree level; "mhs-count-kelompok-lembaga" — Get student count by institution group; "dosen-count" — Get total lecturer count; "dosen-count-active" — Get active lecturer count; "dosen-count-gender" — Get lecturer count by gender; "dosen-count-bidang" — Get lecturer count by field; "dosen-count-keaktifan" — Get lecturer count by activity; "dosen-count-jenjang" — Get lecturer count by degree; "dosen-count-ikatan" — Get lecturer count by affiliation; "pt-count" — Get total university count; "pt-count-province" — Get university count by province; "pt-count-kelompok-pembina" — Get university count by supervising group; "pt-count-akreditasi" — Get university count by accreditation; "pt-count-bentuk-pt" — Get university count by institution type; "prodi-count" — Get total study program count; "prodi-count-bidang-ilmu-terbanyak" — Get most common study program field; "prodi-count-kelompok-pembina" — Get study program count by supervising group; "prodi-count-bidang-ilmu" — Get study program count by field; "prodi-count-akreditasi" — Get study program count by accreditation; "prodi-count-jenjang" — Get study program count by degree level.

Input Schema

NameRequiredDescriptionDefault
metricYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so safety and repeatability are covered. The description adds that the response is JSON and that no identifier is needed, but says nothing about how the shape differs per metric or about size/latency.

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?

Purpose and scoping constraints are front-loaded, and the long enum mapping is genuinely necessary given the unreadable metric codes. Minor waste remains in the dangling fragment 'Statistic metric.' and the repetition of 'Get ... count' phrasing across entries.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description should say more about what each metric returns — for example whether 'gender' or 'province' metrics yield multi-row breakdowns versus scalars. 'As JSON' alone leaves an agent unable to anticipate the response structure for grouped metrics.

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 0% and the enum values are opaque Indonesian abbreviations, so the description carries the full burden. It supplies an English gloss for every one of the 25 metrics, which is real added meaning, though a few glosses are terse and don't reveal what the output looks like.

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 gives a specific verb and resource ('Fetch one national aggregate statistic for Indonesian higher education as JSON') and pins the scope by ruling out single-institution queries. This clearly separates it from siblings like get_university and get_study_program, which operate on a specific id.

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?

It states when to use it ('country-wide counts') and when not ('not for a single institution'), and notes no id is required. It stops short of naming the specific sibling tools to use for institution-level data, so the routing hint is directional rather than explicit.

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

Deploy Server

Other Tools