What makes 广告数据分析 notable?

1.1K downloads. Trust evidence available

How should 广告数据分析 be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

广告数据分析

广告投放数据分析。当用户上传 Excel/CSV 广告报表，或说"帮我分析投放数据/看看这个报表/哪个计划效果差/数据有没有问题"时触发。自动识别所有表头列，无需预设字段名，汇总全部指标，检测异常，生成可视化图表，输出分析报告和优化建议。支持巨量引擎、腾讯广告、Meta Ads、Google Ads、快手等平台导... Skill: 广告数据分析 Owner: ming0429 Summary: 广告投放数据分析。当用户上传 Excel/CSV 广告报表，或说"帮我分析投放数据/看看这个报表/哪个计划效果差/数据有没有问题"时触发。自动识别所有表头列，无需预设字段名，汇总全部指标，检测异常，生成可视化图表，输出分析报告和优化建议。支持巨量引擎、腾讯广告、Meta Ads、Google Ads、快手等平台导... Tags: advertising:1.0.1, data-analyzer:1.0.2, latest:1.0.2 Version history: v1.0.2 | 2026-04-16T06:11:09.989Z | user **New version adds automated data visualization and script-based analysis.** - Added scripts/analyze.py

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.0.2

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.2release · observed Apr 16, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s174ep1mzq3b0mz7q623kj2wfd84tj1c:ad-analyzer-yima

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-ming0429-ad-analyzer-yima/snapshot"

Documentation

CLAWHUB

12,578 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: ad-analyzer-yima
description: 广告投放数据分析。当用户上传 Excel/CSV 广告报表，或说"帮我分析投放数据/看看这个报表/哪个计划效果差/数据有没有问题"时触发。自动识别所有表头列，无需预设字段名，汇总全部指标，检测异常，生成可视化图表，输出分析报告和优化建议。支持巨量引擎、腾讯广告、Meta Ads、Google Ads、快手等平台导出格式。
homepage: https://clawhub.ai/ming0429/ad-analyzer-yima
version: 1.1.0
author: guojiaming
tags: [advertising, analytics, excel, csv, 广告分析, 投放优化, 数据可视化, chart]
metadata:
  clawdbot:
    emoji: 📊
    requires:
      bins: [python3]
      pip: [pandas, openpyxl, xlrd, matplotlib, seaborn]
      env: []
---

# 广告数据分析 Skill

分析用户上传的广告报表，自动识别所有列，汇总指标，检测异常，生成图表，输出优化建议。

## Setup

无需任何配置，开箱即用。支持 `.xlsx` / `.xls` / `.csv`，兼容 UTF-8 / GBK 编码。

## Usage

用户上传文件后，将完整分析脚本保存为文件再执行。**不要用 `-c` 内联方式运行**，内联模式不支持多行缩进代码。

正确执行方式：
```bash
# 第一步：把 scripts/analyze.py 脚本保存到本地
# 第二步：执行
python3 analyze.py --file /path/to/report.xlsx --out ./charts
```

## 分析脚本说明

脚本位于 `scripts/analyze.py`，执行后自动完成以下步骤：

1. **读取文件** — 自动识别 xlsx/xls/csv，自动尝试 utf-8/gbk 编码
2. **识别列类型** — 自动区分日期列、维度列（文字）、指标列（数值），不预设列名
3. **汇总指标** — 所有数值列的合计、均值、最大值、最小值
4. **分组分析** — 按每个维度列分组汇总，自动排序
5. **异常检测** — 均值 ±2 倍标准差自动标记异常行
6. **生成图表** — 输出 5 张 PNG 图表
7. **输出建议** — 基于数据给出具体优化方向

## 图表输出

| 文件名 | 内容 |
|--------|------|
| chart_1_totals.png | 各指标总量柱状图 |
| chart_2_dim_compare.png | 主维度横向对比图 |
| chart_3_trend.png | 指标趋势折线图（有日期列时） |
| chart_4_correlation.png | 指标相关性热力图（指标≥3时） |
| chart_5_pie.png | 主维度占比饼图 |

## Notes

- 必须保存为 `.py` 文件执行，不支持 `python3 -c` 内联模式
- 完全动态识别列名，表头是什么分析什么，一列不漏
- 数据不外传，完全本地处理
- 编码自动识别，兼容国内广告平台导出文件

## Examples

分析巨量引擎报表：
```bash
python3 analyze.py --file ~/Downloads/report.xlsx --out ~/Desktop/charts
```

分析腾讯广告 CSV：
```bash
python3 analyze.py --file ~/Downloads/tencent.csv --out ~/Desktop/charts
```

_meta.json

{
  "ownerId": "kn75qh8ba8e3ekf513rveqqstx84tt20",
  "slug": "ad-analyzer-yima",
  "version": "1.0.2",
  "publishedAt": 1776319869989
}

skill-card.md

## Description:

广告投放数据分析。当用户上传 Excel/CSV 广告报表，或说"帮我分析投放数据/看看这个报表/哪个计划效果差/数据有没有问题"时触发。自动识别所有表头列，无需预设字段名，汇总全部指标，检测异常，生成可视化图表，输出分析报告和优化建议。支持巨量引擎、腾讯广告、Meta Ads、Google Ads、快手等平台导出格式。

This skill is ready for commercial/non-commercial use.

## Publisher:

[ming0429](https://clawhub.ai/user/ming0429)

### License/Terms of Use:

MIT-0

## Use Case:

Marketing operators, analysts, and agent users can use this skill to analyze user-provided advertising Excel or CSV reports, identify metrics and anomalies, generate local charts, and draft optimization guidance across common ad-platform export formats.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Advertising reports can contain sensitive business data.

Mitigation: Run the analyzer only on reports intentionally provided by the user and keep generated chart files in an appropriate local output folder.

Risk: Automated optimization suggestions may be incomplete or misleading for business decisions.

Mitigation: Review the generated recommendations against campaign context before changing budgets, pausing ads, or reallocating spend.

Risk: The skill installs standard Python data-analysis packages and writes PNG outputs.

Mitigation: Use a trusted Python environment and choose an output directory where generated chart files are expected.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/ming0429/skills/ad-analyzer-yima)

## Skill Output:

**Output Type(s):** [Text, Shell commands, Code, Files, Guidance]

**Output Format:** [Markdown guidance with bash command examples, console analysis text, and local PNG chart files]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Requires python3 plus pandas, openpyxl, xlrd, matplotlib, and seaborn; reads user-provided Excel/CSV files locally and writes charts to the selected output directory.]

## Skill Version(s):

1.0.2 (source: server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

Github ReposUpdated 2d agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.

MCPOPENCLAW

Github ReposUpdated 7mo agoRank 70

CopilotKit

The Frontend for Agents & Generative UI. React + Angular