name: Business Intelligence slug: business-intelligence version: 1.0.0 homepage: https://clawic.com/skills/business-intelligence description: Model business performance, define KPIs, and turn data into decision-ready dashboards, briefings, and operating cadences for teams and executives. changelog: Initial release with metric tree modeling, KPI contracts, dashboard specifications, and decision briefing workflows. metadata: {"clawdbot":{"emoji":"B","requires":{"bins":[]},"os":["linux","darwin","win32"]}}
On first use, read setup.md for integration behavior and memory initialization.
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".
Working memory lives in ~/business-intelligence/. See memory-template.md for base structure and status behavior.
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~/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
Load only the file needed for the current task to keep context focused.
| Topic | File |
|---|---|
| Setup and integration | setup.md |
| Memory schema | memory-template.md |
| Objective and metric tree design | metric-tree.md |
| KPI definition contracts | kpi-dictionary.md |
| Dashboard and drill-down design | dashboard-specs.md |
| Decision brief templates | insight-briefs.md |
| Review rituals and escalation rules | decision-cadence.md |
| Source quality and data contracts | data-contracts.md |
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.
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.
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.
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.
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.
Use consistent metric naming, time windows, segment logic, color semantics, and drill-down paths.
Inconsistent dashboard specs make cross-team comparisons invalid.
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.
This skill makes NO external network requests.
| Endpoint | Data Sent | Purpose |
|---|---|---|
| None | None | N/A |
No data is sent externally.
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.
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.
clawhub star business-intelligenceclawhub sync这个技能质量优秀,提供了完整的商业智能方法体系。从定义关键指标到建立决策节奏,每个环节都有清晰标准。最突出的是强调“从决策问题出发”而非追求炫酷图表,以及KPI合约确保团队对指标理解一致。内存管理让跨会话协作更顺畅。上手需要一定学习成本,文档缺少实际使用案例参考,但整体专业度和实用性都很高。