code-execution-fallback-e81068

Fallback instructions for running Python from a saved script when the code-execution sandbox fails repeatedly. It switches from sandbox execution to writing a .py file and running it from the command line.

In plain words
What is it for?
Saving Python code to a file, adding basic error handling and output, and executing it through the shell after at least two sandbox failures.
Why use it?
It provides another way to run code after repeated unknown errors, timeouts, or sandbox problems.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/hkuds/openspace/code-execution-fallback-e81068
Any agent
npx skills add HKUDS/OpenSpace --skill code-execution-fallback-e81068
Clone the repo
git clone --depth 1 https://github.com/HKUDS/OpenSpace

Made for: Claude Code, Codex.

Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 973 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.00973
Opus 5 $0.00011 $0.00487
Sonnet 5 $0.00004 $0.00195
Haiku 4.5 $0.00002 $0.00097

Measured 2d ago against content hash ddf23bd77455, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-execution-fallback-e81068 scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

benchmarks/gdpval/skills/code-execution-fallback-e81068/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Execution Fallback Workflow

When to Use

Use this skill when execute_code_sandbox fails repeatedly (2+ attempts) with unknown, persistent, or unexplained errors. This fallback approach uses write_file + run_shell to save Python scripts to disk and execute them via command line, which has proven more reliable in certain failure scenarios.

Step-by-Step Instructions

Step 1: Detect Repeated Failures

Monitor execute_code_sandbox attempts. After 2 consecutive failures with errors like:

  • "Unknown error"
  • Timeout errors
  • Unexplained execution failures
  • Sandbox environment issues

Switch to the fallback workflow immediately.

Step 2: Write the Python Script to File

Use write_file to save your Python code as a .py file in the working directory:

write_file(
    path="script.py",
    content="""
import sys
import json

# Your Python code here
def main():
    # Your logic
    result = {"status": "success", "data": "example"}
    print(json.dumps(result))

if __name__ == "__main__":
    main()
"""
)

Tips:

  • Use clear, self-contained code that doesn't rely on sandbox-specific paths
  • Include error handling and informative print statements
  • Save output to files if needed for later retrieval

Step 3: Execute via Shell

Use run_shell to execute the Python script via command line:

run_shell(
    command="python3 script.py",
    timeout=60  # Adjust timeout as needed
)

Alternative commands:

  • python script.py - if python3 alias isn't available
  • python3 -u script.py - for unbuffered output
  • python3 script.py arg1 arg2 - with arguments

Step 4: Verify Output and Results

Check the stdout/stderr from run_shell to:

  • Confirm execution succeeded (exit code 0)
  • Inspect printed output or results
  • Identify any new errors (different from sandbox errors)

If the script writes output files, use read_file to retrieve results.

Step 5: Clean Up (Optional)

Remove temporary script files if they won't be reused:

Read the full file on GitHub · 143 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 143 lines · 22 tokens per session scan A ddf23bd77455

Subscribe to this mod's changes

code-execution-fallback-e81068 is a skill published in the GitHub repository HKUDS/OpenSpace (7,479 stars, last pushed 20d ago), licensed MIT. It adds 22 tokens to every session and 973 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens