code-exec-fallback

code-exec-fallback is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 18 tokens per session (550 once invoked), scanned A, original, MIT.

A fallback procedure for running Python code through a shell when a code-execution sandbox repeatedly fails. It saves the script, runs it with Python, and captures the result.

In plain words
What is it for?
Use it to create a temporary Python script, run it with Python 3, inspect errors and output, and optionally remove the script afterward.
Why use it?
It gives you another way to execute code when the usual sandbox has timeouts, missing dependencies, or environment restrictions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create a temporary Python script, run it with Python 3, inspect errors and output, and optionally remove the script afterward.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hkuds/openspace/code-exec-fallback
About the project

OpenSpace is a skill-management layer for AI agents that stores, retrieves, evaluates, shares, and improves reusable workflows. It is intended for people using multiple coding agents who want skills to be reused and refined based on task outcomes. The catalogue provides 200 skills for use with OpenSpace and the agents it supports.

HKUDS/OpenSpace · 7,760 stars · on GitHub

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.

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

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for code-exec-fallback

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/code-exec-fallback/github.svg)](https://agentmods.dev/skills/hkuds/openspace/code-exec-fallback)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/code-exec-fallback"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/code-exec-fallback/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for code-exec-fallback

Your own site · 80×15
<a href="https://agentmods.dev/skills/hkuds/openspace/code-exec-fallback"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/code-exec-fallback.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 550 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00018 $0.00550
Opus 5.5 $0.00007 $0.00220
Sonnet 5.5 $0.00004 $0.00110
Haiku 4.5 $0.00002 $0.00055

Measured 1mo ago against content hash c9406cfed5a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-exec-fallback 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 1mo 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-exec-fallback/SKILL.md · 80 lines

What it actually says

Code Execution Fallback

When to Use

Use this pattern when execute_code_sandbox fails repeatedly (typically 2+ attempts) due to environment limitations, timeouts, dependency issues, or sandbox restrictions.

The Pattern

Instead of executing code directly in the sandbox, write the Python script to a file and execute it via shell:

  1. Write the script using write_file
  2. Execute via shell using run_shell with python3 script.py
  3. Clean up (optional) remove the temporary file

Step-by-Step Instructions

Step 1: Write the Python Script

Use write_file to save your Python code:
- Path: Choose a descriptive name (e.g., "process_data.py", "analyze.py")
- Content: Your complete Python script with all imports and logic

Step 2: Execute via Shell

Use run_shell to execute:
- Command: "python3 <script_name>.py"
- Timeout: Set appropriately for your task (default 30s, increase if needed)

Step 3: Handle Output

- Capture stdout/stderr from run_shell
- Parse results as needed
- Optionally delete the script file after execution

Example

# Instead of this (which may fail):
execute_code_sandbox(code="import pandas as pd; df = pd.read_csv('data.csv')...")

# Do this:
write_file(path="analyze.py", content="""
import pandas as pd
import json

df = pd.read_csv('data.csv')
result = df.groupby('category').sum()
print(json.dumps(result.to_dict()))
""")

run_shell(command="python3 analyze.py", timeout=60)

Tips for Success

  1. Include all imports in the script file - the shell environment may differ from the sandbox
  2. Use absolute paths or ensure working directory is correct
  3. Add error handling to your script for better debugging
  4. Increase timeout for long-running operations (default is 30s)
  5. Print structured output (JSON) if you need to parse results
  6. Clean up temporary files after successful execution to avoid clutter

When This Helps

  • Sandbox has missing dependencies
  • Code execution times out in sandbox but would work in shell
  • File I/O operations are restricted in sandbox
  • Need to run external commands or system utilities
  • Complex multi-file projects that need proper file structure
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. 1mo ago First seen · 80 lines · 18 tokens per session scan A c9406cfed5a8

Subscribe to this mod's changes

code-exec-fallback is a skill published in the GitHub repository HKUDS/OpenSpace (7,760 stars, last pushed 2mo ago), licensed MIT. It adds 18 tokens to every session and 550 once invoked, about $0.0001 per session on Opus 5.5. 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

matlab

Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 44 tokens

pennylane

Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for…

K-Dense-AI/scientific-agent-skills · 74 tokens

rocm-kernels

Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline…

huggingface/kernels · 93 tokens

holoscan-install-wheel

Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.

NVIDIA/skills · 37 tokens

typing-exclusion-worker

Python typing exclusion worker: remove assigned mypy exclusion modules in small scoped batches, fix typing issues, run validation, and produce a structured completion summary. Use when running parallel typing-debt workers or when asked to remove modules from pyproject mypy exclusion overrides.

getsentry/skills · 57 tokens

python

Python development with ruff, mypy, pytest - TDD and type safety.

alinaqi/maggy · 18 tokens