analyzing-data

📁 astronomer/agents 📅 Jan 23, 2026
194
总安装量
194
周安装量
#1380
全站排名
安装命令
npx skills add https://github.com/astronomer/agents --skill analyzing-data

Agent 安装分布

claude-code 125
opencode 116
codex 112
github-copilot 109
cursor 99
gemini-cli 96

Skill 文档

Data Analysis

Answer business questions by querying the data warehouse. The kernel auto-starts on first exec call.

All CLI commands below are relative to this skill’s directory. Before running any scripts/cli.py command, cd to the directory containing this file.

Workflow

  1. Pattern lookup — Check for a cached query strategy:

    uv run scripts/cli.py pattern lookup "<user's question>"
    

    If a pattern exists, follow its strategy. Record the outcome after executing:

    uv run scripts/cli.py pattern record <name> --success  # or --failure
    
  2. Concept lookup — Find known table mappings:

    uv run scripts/cli.py concept lookup <concept>
    
  3. Table discovery — If cache misses, search the codebase (Grep pattern="<concept>" glob="**/*.sql") or query INFORMATION_SCHEMA. See reference/discovery-warehouse.md.

  4. Execute query:

    uv run scripts/cli.py exec "df = run_sql('SELECT ...')"
    uv run scripts/cli.py exec "print(df)"
    
  5. Cache learnings — Always cache before presenting results:

    # Cache concept → table mapping
    uv run scripts/cli.py concept learn <concept> <TABLE> -k <KEY_COL>
    # Cache query strategy (if discovery was needed)
    uv run scripts/cli.py pattern learn <name> -q "question" -s "step" -t "TABLE" -g "gotcha"
    
  6. Present findings to user.

Kernel Functions

Function Returns
run_sql(query, limit=100) Polars DataFrame
run_sql_pandas(query, limit=100) Pandas DataFrame

pl (Polars) and pd (Pandas) are pre-imported.

CLI Reference

Kernel

uv run scripts/cli.py warehouse list      # List warehouses
uv run scripts/cli.py start [-w name]     # Start kernel (with optional warehouse)
uv run scripts/cli.py exec "..."          # Execute Python code
uv run scripts/cli.py status              # Kernel status
uv run scripts/cli.py restart             # Restart kernel
uv run scripts/cli.py stop                # Stop kernel
uv run scripts/cli.py install <pkg>       # Install package

Concept Cache

uv run scripts/cli.py concept lookup <name>                     # Look up
uv run scripts/cli.py concept learn <name> <TABLE> -k <KEY_COL> # Learn
uv run scripts/cli.py concept list                               # List all
uv run scripts/cli.py concept import -p /path/to/warehouse.md   # Bulk import

Pattern Cache

uv run scripts/cli.py pattern lookup "question"                                      # Look up
uv run scripts/cli.py pattern learn <name> -q "..." -s "..." -t "TABLE" -g "gotcha"  # Learn
uv run scripts/cli.py pattern record <name> --success                                # Record outcome
uv run scripts/cli.py pattern list                                                   # List all
uv run scripts/cli.py pattern delete <name>                                          # Delete

Table Schema Cache

uv run scripts/cli.py table lookup <TABLE>            # Look up schema
uv run scripts/cli.py table cache <TABLE> -c '[...]'  # Cache schema
uv run scripts/cli.py table list                       # List cached
uv run scripts/cli.py table delete <TABLE>             # Delete

Cache Management

uv run scripts/cli.py cache status                # Stats
uv run scripts/cli.py cache clear [--stale-only]  # Clear

References