菜单
Query aggregated analytics data from DHIS2. Use for calculated/aggregated values, indicator values, or cross-dimensional analysis. ALWAYS use with dhis2-query-optimization skill. Routed via dhis2 skill for general DHIS2 requests.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/BLSQ/mcp_servers --skill dhis2-analytics命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Guide for creating OpenHEXA data pipelines. Use when users ask to create a pipeline, build a data pipeline, automate data processing, or schedule data workflows.
Work with DHIS2 health information systems - extract data, query metadata, run validations, manage users, or check system info. Use this skill for ANY DHIS2-related request. It routes to specialized sub-skills and provides centralized client setup and API patterns.
Extract data elements and data element groups from DHIS2. Use for data element metadata, groups, or category option combos. Routed via dhis2 skill for general DHIS2 requests.
正在显示 SKILL.md
基于 SOC 职业分类
| name | dhis2-analytics |
| description | Query aggregated analytics data from DHIS2. Use for calculated/aggregated values, indicator values, or cross-dimensional analysis. ALWAYS use with dhis2-query-optimization skill. Routed via dhis2 skill for general DHIS2 requests. |
Prerequisites: Client setup from dhis2 skill + dhis2-query-optimization for large queries
from openhexa.toolbox.dhis2 import dataframe
| Parameter | Type | Required | Notes |
|---|---|---|---|
| dhis2 | DHIS2 | Yes | |
| periods | list[str] | Yes | e.g., ["2021", "202401"] |
| data_elements | list[str] | None | No | Cannot mix with indicators |
| data_element_groups | list[str] | None | No | Cannot mix with indicators |
| indicators | list[str] | None | No | Cannot mix with data_elements |
| indicator_groups | list[str] | None | No | Cannot mix with data_elements |
| org_units | list[str] | None | No | At least one spatial dim required |
| org_unit_groups | list[str] | None | No | At least one spatial dim required |
| org_unit_levels | list[int] | None | No | At least one spatial dim required |
Returns pl.DataFrame:
For data elements:
| Column | Type |
|---|---|
| data_element_id | str |
| category_option_combo_id | str |
| organisation_unit_id | str |
| period | str |
| value | str |
For indicators (no category_option_combo_id):
| Column | Type |
|---|---|
| indicator_id | str |
| organisation_unit_id | str |
| period | str |
| value | str |
# Data elements
data = dhis.analytics.get(
data_elements=["uid"],
org_units=["uid"],
periods=["202401"]
) # Returns list[dict]
# Indicators - ALWAYS use include_cocs=False
data = dhis.analytics.get(
indicators=["uid"],
org_units=["uid"],
periods=["2024"],
include_cocs=False # MANDATORY for indicators
)