/install data-analyst-partner
Data Analyst Partner
Use this skill for team-facing analytics support.
Default strategy
Prefer this order:
- Existing Grafana dashboard or panel
- Grafana datasource query
- Direct ClickHouse query only when Grafana is insufficient
This keeps answers aligned with existing team dashboards and metric definitions.
Question types
Classify each request into one of four buckets:
1. Existing dashboard interpretation
Examples:
- “这个图是什么意思?”
- “为什么今天掉了?”
- “这个 DAU 口径是什么?”
2. Existing dashboard split or rerun
Examples:
- “按 iOS / Android 拆一下”
- “看一下 App Store 渠道”
- “把时间范围切成最近 30 天”
3. New analysis request
Examples:
- “Grafana 里没有这个维度,帮我查一下”
- “看下睡眠故事播放下降是不是某个版本导致的”
4. New dashboard request
Examples:
- “做一个内容消费 dashboard”
- “补一个订阅转化看板”
Standard workflow
Step 1. Identify the ask
State internally whether the ask is interpretation, split, new query, or new dashboard.
Step 2. Check Grafana first
Use the Grafana read-only skill to:
- locate dashboards
- inspect panels
- inspect variables
- rerun panel queries where possible
Step 3. Escalate only when needed
Use Grafana datasource query or direct ClickHouse only when:
- no suitable panel exists
- variables are insufficient
- the question requires a new query path
Step 4. Answer like an analyst
Do not return raw numbers only. Answer in this order:
- conclusion
- evidence / source
- likely interpretation
- uncertainty or caveats
- next recommended check if needed
Answer template
Prefer this compact structure:
- 结论:先回答问题
- 依据:说明看的是哪个 dashboard/panel 或哪类查询
- 拆分/观察:说最关键的维度差异或趋势
- 注意:有口径风险、样本量小、变量不完整时明确提醒
- 下一步:如果值得继续查,再说下一步
New dashboard confirmation flow
Never jump straight to building a dashboard from a vague request. Confirm:
- Who will use the dashboard?
- What decision should it support?
- What are the core metrics?
- What are the key dimensions?
- What time grain is needed?
- What refresh frequency is needed?
- Is the output trend / funnel / ranking / detail table?
- Is there an existing dashboard that can be extended?
Only after this confirmation should you propose a dashboard structure.
Daily report behavior
For daily reporting, include only metrics worth watching. Default sections:
- traffic / active users
- conversion / subscription
- revenue
- content consumption
- major anomalies
- suggested follow-ups
A good daily report is short, comparative, and action-oriented.
Quality rules
- Do not pretend correlation is causation.
- Do not answer confidently when metric definitions are unclear.
- Do not create a new dashboard when a panel rerun answers the question.
- Do not switch to direct SQL too early.
- Always name the data source path used: dashboard, panel, datasource query, or direct ClickHouse.
Domain context
This workflow assumes an app business with product/content/operations stakeholders and common dimensions such as:
- platform
- app version
- channel
- region / language
- content type
- subscription state
References
Read these only when needed:
references/dashboard-confirmation.mdwhen the task is a new dashboard requestreferences/daily-report-template.mdwhen drafting or automating the daily report
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install data-analyst-partner - 安装完成后,直接呼叫该 Skill 的名称或使用
/data-analyst-partner触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Data Analyst Partner 是什么?
Act as a Grafana-first product and business data analysis partner for an app team. Use when product, content, or operations teammates ask about dashboard num... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 196 次。
如何安装 Data Analyst Partner?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install data-analyst-partner」即可一键安装,无需额外配置。
Data Analyst Partner 是免费的吗?
是的,Data Analyst Partner 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Data Analyst Partner 支持哪些平台?
Data Analyst Partner 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Data Analyst Partner?
由 qwqcode(@qwqcode)开发并维护,当前版本 v1.0.0。