Skip to main content

build-dashboard

Build a source-backed dashboard or monitoring view with clear metrics, filters, visual hierarchy, definitions, refresh context, and QA.

来源信息

仓库
XiaomiMiMo/MiMo-Code
最近来源活动
2026年9月30日 08:41
检测到的 SKILL.md 语言
英语
星标
13,667
分支
1,448

安装方式

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。

检查来源文件

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。

文件资源管理器
5 个文件

正在显示 SKILL.md

SKILL.md
来源说明 · 只读预览
name
build-dashboard
description
Build a source-backed dashboard or monitoring view with clear metrics, filters, visual hierarchy, definitions, refresh context, and QA.
# Build a Dashboard Use this workflow when the user needs a reusable monitoring or exploration surface rather than a one-time report. Read the relevant analysis and KPI workflows first when metric definitions or decision logic are not already settled. ## Select a portable surface Honor the user's destination. Otherwise choose the simplest surface supported by the harness: - Existing BI/product analytics platform when the user wants a governed shared dashboard there. - Streamlit when Python execution and local/server operation are appropriate; read `specifications/streamlit-dashboard.md`. - Self-contained plain HTML/CSS/vanilla JavaScript for a portable local dashboard; read `specifications/html-dashboard.md`. Do not require React, Vite, Recharts, MCP Apps, or widget runtimes. ## Workflow 1. Define the audience, operating decision, monitoring cadence, and questions the dashboard must answer. 2. Define each metric: formula, numerator/denominator, unit, grain, time window, filters, exclusions, owner, source, and freshness expectation. 3. Validate joins, completeness, duplicates, missingness, comparability, and refresh status before presenting metrics as trustworthy. 4. Design the information hierarchy: - Overview and primary outcomes. - Drivers and diagnostic cuts. - Guardrails and risks. - Detail tables or drill-down paths. 5. Add only decision-relevant filters. Make default date ranges, segments, comparison periods, and filter state visible. 6. Use `../visualize-data/SKILL.md` for each chart and keep exact lookup values accessible in tables. 7. Show data freshness, source context, definitions, and material caveats in the dashboard. 8. Implement and test the real artifact with representative, empty, partial, and error states when feasible. ## QA and handoff - Reconcile displayed totals and KPIs against reviewed source results. - Test filters, date boundaries, sorting, responsive layout, and refresh behavior. - Check chart labels, units, legends, accessibility, and table readability. - Ensure the artifact does not expose secrets, credentials, unnecessary personal data, or temporary local paths. - Deliver the dashboard artifact or governed platform link plus metric definitions, source/query files, refresh instructions, and known limitations.
在 GitHub 查看