Agent Skills
› fastclaw-ai/fastclaw
› data-analysis
data-analysis
GitHub提供基于Python的数据分析与处理能力，支持CSV/JSON文件读取、统计计算及可视化生成。适用于数据处理、统计分析等场景。
Trigger Scenarios
用户请求数据分析
需要处理CSV或JSON文件
要求计算统计数据
需要创建数据可视化图表
Install
npx skills add fastclaw-ai/fastclaw --skill data-analysis -g -y
SKILL.md
Frontmatter
{
"name": "data-analysis",
"metadata": {
"fastclaw": {
"always": false
}
},
"description": "Analyze data, process CSV\/JSON files, compute statistics, and create data visualizations. Use when the user asks about data processing, statistics, or analysis."
}
Data Analysis Skill
Analyze and process data using Python in the sandbox.
Common Libraries
- pandas: DataFrames, CSV/JSON/Excel processing
- numpy: Numerical computing
- matplotlib: Visualization (use Agg backend)
Install if needed: pip install pandas numpy matplotlib
Common Tasks
Read and analyze CSV
import pandas as pd
df = pd.read_csv('data.csv')
print(df.describe())
print(f"\nShape: {df.shape}")
print(f"\nColumns: {list(df.columns)}")
print(f"\nFirst 5 rows:\n{df.head()}")
Create visualization from data
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import pandas as pd
import base64
df = pd.read_csv('data.csv')
df.plot(kind='bar', x='category', y='value', figsize=(10, 6))
plt.title('Data Overview')
plt.tight_layout()
plt.savefig('/tmp/chart.png', dpi=150)
with open('/tmp/chart.png', 'rb') as f:
print(f').decode()})')
JSON processing
import json
with open('data.json') as f:
data = json.load(f)
# Process and analyze...
Guidelines
- Always execute the analysis — don't just show code
- Show key statistics: shape, dtypes, describe(), null counts
- For large datasets, show head/tail and summary stats
- Generate charts when it helps explain the data
- Use base64 inline images for any visualizations
Version History
- beee30c Current 2026-07-25 08:17
