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business-intelligence商业智能

Agent Skill

business-intelligence 用于补充开发相关能力,适合在 Local Agent 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

196

周安装

8

下载量

63
Local Agent

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:business-intelligence(商业智能)
来源仓库:https://skills.volces.com
仓库路径:business-intelligence
安装命令:
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。当前暂无明确安装命令,请以来源页面说明为准。

简介

business-intelligence 用于补充开发相关能力,适合在 Local Agent 中处理数据分析任务。

  • 它帮助 Agent 整合数据源、生成报表或发现业务洞察。
  • 使用时需结合具体数据结构和查询需求进行适配。
  • 安装前应确认是否会访问数据库或导出文件。
  • 建议评估数据安全性和权限控制后再启用。

SKILL.md

Setup

On first use, read setup.md for integration behavior and memory initialization.

When to Use

Use this skill when the user needs to build or improve business intelligence systems: KPI definitions, metric architecture, dashboard planning, executive reporting, and decision review loops.

This skill is optimized for operators, founders, product leaders, finance leaders, and analysts who need clear answers to "what changed, why it changed, and what to do next".

Architecture

Working memory lives in ~/business-intelligence/. See memory-template.md for base structure and status behavior.

~/business-intelligence/
├── memory.md                # HOT: goals, KPI ownership, active decisions
├── metric-tree/             # WARM: objective -> driver -> metric maps
├── kpi-contracts/           # WARM: metric definitions and formula versions
├── dashboard-specs/         # WARM: visualization and drill-down specifications
├── insight-briefs/          # WARM: weekly and monthly decision briefs
├── operating-cadence/       # WARM: review rituals and escalation rules
└── archive/                 # COLD: retired KPIs and past planning cycles

Quick Reference

Load only the file needed for the current task to keep context focused.

TopicFile
Setup and integrationsetup.md
Memory schemamemory-template.md
Objective and metric tree designmetric-tree.md
KPI definition contractskpi-dictionary.md
Dashboard and drill-down designdashboard-specs.md
Decision brief templatesinsight-briefs.md
Review rituals and escalation rulesdecision-cadence.md
Source quality and data contractsdata-contracts.md

Core Rules

1. Start from Decision Questions, Not Charts

Every BI request must begin with one decision question and one owner.

If there is no decision owner, the output is reporting noise and should be reframed before building metrics.

2. Build a Metric Tree Before Dashboard Design

Map each business objective to drivers, then drivers to measurable KPIs.

Do not build dashboards first. Dashboards without a metric tree create disconnected charts and contradictory narratives.

3. Enforce KPI Contracts

Each KPI needs a written contract: definition, formula, grain, source, refresh cadence, owner, and valid interpretation window.

Never compare KPI values across periods if formula version or source logic changed without annotation.

4. Separate Leading and Lagging Indicators

For every lagging KPI, define at least one leading indicator that signals future movement.

If the system only tracks lagging outcomes, intervention happens too late.

5. Brief Insights in Decision Format

Every insight output must include:

  • What changed
  • Why it changed
  • Confidence level
  • Recommended action
  • Action owner and due date

A BI summary without an action owner is incomplete.

6. Standardize Dashboard Specs Across Teams

Use consistent metric naming, time windows, segment logic, color semantics, and drill-down paths.

Inconsistent dashboard specs make cross-team comparisons invalid.

7. Run a Fixed Operating Cadence

Define daily, weekly, monthly, and quarterly BI rituals with clear participants and escalation triggers.

Without a fixed cadence, KPI review becomes reactive and decision quality degrades.

Business Intelligence Traps

  • Starting with visualization tooling before KPI contracts -> expensive dashboards with weak decisions.
  • Tracking too many KPIs per objective -> teams lose focus on actual drivers.
  • Blending forecast assumptions with actuals in one number -> executives make false confidence calls.
  • Changing formulas without version notes -> historical trend comparisons become invalid.
  • Reporting movement without attribution depth -> teams cannot identify correct interventions.
  • Sending BI updates without action owners -> insights do not convert into execution.

External Endpoints

This skill makes NO external network requests.

EndpointData SentPurpose
NoneNoneN/A

No data is sent externally.

Security & Privacy

Data that leaves your machine:

  • Nothing by default.

Data that stays local:

  • BI context, KPI contracts, and reporting notes under ~/business-intelligence/.
  • Decision cadence and retrospective notes stored locally when memory is enabled.

This skill does NOT:

  • Access files outside ~/business-intelligence/ for memory storage.
  • Transmit metrics or business data to third-party APIs by default.
  • Create background automations without explicit user confirmation.
  • Modify its own skill definition files.

Related Skills

Install with clawhub install <slug> if user confirms:

  • analytics - analysis workflows for interpreting performance patterns.
  • data-analysis - analysis workflows for modeling trends, segments, and causal signals.
  • dashboard - dashboard implementation for KPI visualization layers.
  • strategy - strategic planning frameworks tied to business outcomes.
  • report - structured report generation for stakeholder communication.

Feedback

  • If useful: clawhub star business-intelligence
  • Stay updated: clawhub sync

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Local Agent

79.69%
按下载量换算50

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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