Skip to content
cccskills
FreePublished on GitHub

shell-python-heredoc

Run multi-line Python scripts through run_shell when execute_code_sandbox repeatedly fails. The guide explains heredocs, a way to pass blocks of text to a command, with examples for PDF creation, data processing, and inspecting errors.

OriginalShow the original description

Execute complex Python code via run_shell heredoc when execute_code_sandbox fails

See how to install

Good for

  • Running Python after repeated sandbox errors
  • Creating a PDF with ReportLab
  • Summarizing CSV data with pandas
  • Inspecting script output and errors

Files included (2)

  • SKILL.md2.9 KB
  • .skill_id34 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Shell Python Heredoc (Fallback Pattern)

Overview

When execute_code_sandbox fails repeatedly (e.g., with "unknown error"), use run_shell with a Python heredoc as a reliable fallback for executing multi-line Python scripts with imports.

When to Use

  • execute_code_sandbox has failed 2+ times with unexplained errors
  • You need to run Python code with multiple imports (e.g., ReportLab, pandas)
  • The script is too complex for a one-liner but doesn't require persistence between calls
  • You need better error visibility from raw stdout/stderr

How to Use

Basic Pattern

run_shell(
    command="""python3 << 'EOF'
import sys
# Your Python code here
print("Hello from heredoc")
EOF""",
    timeout=300
)

Key Syntax Rules

  1. Use << 'EOF' (with single quotes) to prevent shell variable expansion
  2. Indent Python code relative to the heredoc delimiter
  3. End with EOF on its own line (no leading whitespace)
  4. Capture output from stdout/stderr for debugging

Example: Generating a PDF with ReportLab

run_shell(
    command="""python3 << 'EOF'
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("output.pdf", pagesize=letter)
c.drawString(100, 750, "Hello PDF")
c.save()
print("PDF created successfully")
EOF""",
    timeout=300
)

Example: Multi-file Data Processing

run_shell(
    command="""python3 << 'EOF'
import pandas as pd
import json

# Load and process data
df = pd.read_csv("data.csv")
summary = df.describe()

# Output results
print(summary.to_string())
with open("summary.json", "w") as f:
    json.dump(summary.to_dict(), f)
print("Processing complete")
EOF""",
    timeout=300
)

Advantages Over execute_code_sandbox

  • More reliable for complex imports (no sandbox isolation issues)
  • Full stdout/stderr access for debugging
  • Longer timeout flexibility (60s default vs 30s)
  • Direct filesystem access without ARTIFACT_PATH indirection

Disadvantages

  • No persistent state between calls (each heredoc is a fresh process)
  • Verbose for simple one-liners
  • Shell escaping may be needed for complex string literals

Troubleshooting

IssueSolution
EOF not recognizedEnsure EOF is on its own line with no leading spaces
Import errorsVerify packages are installed in the shell environment
File not foundUse absolute paths or check working directory with pwd
Syntax errorsCheck Python indentation within heredoc

See Also

  • Use execute_code_sandbox for simpler scripts when available
  • Use shell_agent for tasks requiring autonomous iteration and error recovery
  • Consider writing scripts to .py files for complex, reusable code

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Prepare audio stems, the separate parts of a track, for mixing by matching their durations with silence, loops, or crossfades. Verify each generated and processed file before moving to the next production step.

  • Match audio parts with different durations
  • Extend drums and melodic parts using suitable methods
  • Check audio specifications before mixing
HKUDS/OpenSpace7.8KUpdated Aug 13, 2026

Produce audio in separate stems, meaning individual instrument tracks, and verify each output as you go. Align track lengths with silence, loops, or crossfades, then apply effects, mix a master, and package the files.

  • Align instrument tracks to a reference audio file
  • Choose how to extend tracks that are too short
  • Verify audio properties after generation and effects
HKUDS/OpenSpace7.8KUpdated Aug 13, 2026

Build serverless endpoints that relay external API requests for a dashboard while keeping API keys on the server. Includes Vercel examples for input checks, caching, cross-origin access, and consistent JSON responses.

  • Connect a dashboard to external APIs without exposing API keys
  • Create endpoints for stock quotes and news
  • Standardize API responses and error handling
HKUDS/OpenSpace7.8KUpdated Aug 13, 2026

Produce a master track and separate audio parts through a structured Python workflow. Apply filters and reverb, export WAV files with consistent settings, package them in a ZIP archive, and check that the deliverables meet the requested specifications.

  • Export a master track with separate audio parts
  • Apply filters and reverb to audio
  • Check duration and format across deliverables
HKUDS/OpenSpace7.8KUpdated Aug 13, 2026

Keep document creation moving when web searches and page retrieval repeatedly fail. The skill preserves the original task, uses the model’s existing knowledge, and clearly identifies information that could not be checked against external sources.

  • Continue drafting after repeated web retrieval failures
  • Preserve task requirements during network errors
  • Mark information that could not be externally verified
HKUDS/OpenSpace7.8KUpdated Aug 13, 2026

When Python execution repeatedly fails in execute_code_sandbox, use a file-based alternative: save the script, run it through the shell, and capture results or errors. The guidance covers paths, imports, timeouts, structured output, and optional cleanup.

  • Retry Python work through the shell after repeated sandbox failures
  • Run longer tasks with an adjusted timeout
  • Execute Python work that needs multiple files or system utilities
HKUDS/OpenSpace7.8KUpdated Aug 13, 2026

See all skills by HKUDS

Report a problem with this skill