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.
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.
npx skills add HKUDS/OpenSpace --skill python-shell-workaroundgit clone --depth 1 https://github.com/HKUDS/OpenSpaceWrote 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.
[](https://agentmods.dev/skills/hkuds/openspace/python-shell-workaround)<a href="https://agentmods.dev/skills/hkuds/openspace/python-shell-workaround"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/python-shell-workaround.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.00710 |
| Opus 5 | $0.00009 | $0.00355 |
| Sonnet 5 | $0.00003 | $0.00142 |
| Haiku 4.5 | $0.00002 | $0.00071 |
Grade A, and why
python-shell-workaround 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Shell Workaround
When to Use This Skill
Use this pattern when execute_code_sandbox fails with Python code that requires external packages (like openpyxl, python-docx, pandas, etc.) that may not be available in the sandbox environment.
The Pattern
Instead of relying solely on execute_code_sandbox, use run_shell with inline Python commands as a fallback:
python3 -c "your python code here"
Step-by-Step Instructions
Step 1: Detect Sandbox Failure
Watch for errors like:
- ModuleNotFoundError for common packages
- Import errors for external libraries
- Sandbox environment limitations
Step 2: Convert Python Code to Shell Command
Transform your Python script into a one-liner or use a heredoc for longer scripts:
For simple code:
python3 -c "import openpyxl; wb = openpyxl.Workbook(); wb.save('file.xlsx')"
For complex code (using heredoc):
python3 << 'EOF'
import openpyxl
from openpyxl.utils import get_column_letter
wb = openpyxl.Workbook()
ws = wb.active
ws['A1'] = 'Header'
wb.save('output.xlsx')
print('File created successfully')
EOF
Step 3: Execute with run_shell
Use run_shell to execute the command:
tool: run_shell
command: python3 -c "import openpyxl; print('Package available')"
Step 4: Verify Output
Check the stdout/stderr from run_shell to confirm success, then proceed with subsequent steps.
Best Practices
- Escape quotes properly: Use single quotes inside double-quoted strings or vice versa
- Use heredocs for multiline code: Cleaner and easier to debug
- Install packages if needed: Add
pip install packagebefore your Python command if packages are missing - Chain commands safely: Use
&&to ensure prerequisites succeed before running Python code
Example Scenarios
Creating Excel Files
python3 << 'EOF'
import openpyxl
from openpyxl.worksheet.datavalidation import DataValidation
wb = openpyxl.Workbook()
ws = wb.active
ws.title = "Data"
# Add headers
headers = ['Name', 'Email', 'Status']
for col, header in enumerate(headers, 1):
ws.cell(row=1, column=col, value=header)
wb.save('output.xlsx')
EOF
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.
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.
- 3d ago First seen · 113 lines · 17 tokens per session scan A cbdd5e16c912
python-shell-workaround is a skill published in the GitHub repository HKUDS/OpenSpace (7,510 stars, last pushed 25d ago), licensed MIT. It adds 17 tokens to every session and 710 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 2026-09-03.
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