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 run-shell-fallbackgit 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/run-shell-fallback)<a href="https://agentmods.dev/skills/hkuds/openspace/run-shell-fallback"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/run-shell-fallback.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.01026 |
| Opus 5 | $0.00012 | $0.00513 |
| Sonnet 5 | $0.00005 | $0.00205 |
| Haiku 4.5 | $0.00002 | $0.00103 |
Grade A, and why
run-shell-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 4d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run Shell Fallback Pattern
This skill provides a reliable workaround when execute_code_sandbox or read_file fail with 'unknown error' by switching to run_shell with inline Python code.
When to Use
Apply this pattern when you encounter:
execute_code_sandboxfails with "unknown error" or timeoutread_filefails to read accessible files with "unknown error"- Sandbox environment is unreliable for your specific task
How to Implement
1. File Reading Fallback
When read_file fails, use run_shell with Python or cat:
For text files:
run_shell(command="cat /path/to/file.txt")
For structured parsing (Python one-liner):
run_shell(command="python3 -c \"import json; print(json.load(open('/path/to/file.json')))\"")
For multi-line Python processing:
run_shell(command="python3 << 'EOF'
with open('/path/to/file.txt', 'r') as f:
content = f.read()
# Process content here
print(content.upper())
EOF")
2. Code Execution Fallback
When execute_code_sandbox fails, use run_shell with inline Python:
Simple one-liners:
run_shell(command="python3 -c \"print('Hello'); import os; print(os.getcwd())\"")
Multi-line scripts (heredoc):
run_shell(command="python3 << 'EOF'
import os
import json
def process_data(data):
return {k: v.upper() if isinstance(v, str) else v for k, v in data.items()}
with open('input.json') as f:
data = json.load(f)
result = process_data(data)
print(json.dumps(result, indent=2))
EOF")
With inline file write:
run_shell(command="python3 << 'EOF'
result = {'status': 'success', 'count': 42}
with open('output.json', 'w') as f:
json.dump(result, f, indent=2)
print('File written successfully')
EOF")
3. Decision Flow
1. Attempt execute_code_sandbox or read_file
2. If failure with 'unknown error':
a. Determine task type (code execution vs file reading)
b. Choose inline Python approach (-c for simple, heredoc for complex)
c. Execute via run_shell
d. Parse output as needed
3. Continue with task using results from run_shell
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.
- 4d ago First seen · 142 lines · 24 tokens per session scan A cccd6e62fa9e
run-shell-fallback is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 26d ago), licensed MIT. It adds 24 tokens to every session and 1,026 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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