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 spreadsheet-direct-python-enhancedgit 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/spreadsheet-direct-python-enhanced)<a href="https://agentmods.dev/skills/hkuds/openspace/spreadsheet-direct-python-enhanced"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/spreadsheet-direct-python-enhanced.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 | $0.01345 |
| Opus 5 | $0.00012 | $0.00673 |
| Sonnet 5 | $0.00005 | $0.00269 |
| Haiku 4.5 | $0.00002 | $0.00135 |
Grade A, and why
spreadsheet-python-file-exec 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Direct Python Execution for Spreadsheet Tasks
When to Use This Skill
Use direct run_shell with Python scripts for spreadsheet operations when:
- Reading or writing complex Excel files with multiple sheets
- Applying formulas, formatting, or data transformations
- Working with
openpyxl,pandas, or similar libraries - The operation involves multiple steps that could exceed agent step limits
- You need precise control over error handling and debugging
- Complex scripts benefit from file-based execution for better reliability
Why Direct Execution?
The shell_agent tool can:
- Hit maximum step limits on complex multi-step operations
- Produce unexplained errors on formatting operations
- Fail on intricate spreadsheet reads/writes due to iterative parsing
- Fail to parse heredoc syntax correctly, causing 'unknown error' failures
Direct run_shell with Python is more reliable because it:
- Executes in a single step with no iteration limits
- Provides clearer, immediate error messages
- Handles complex operations without step constraints
- Gives full control over library imports and execution flow
- Writing scripts to
.pyfiles first avoids shell_agent parsing issues with heredocs
How to Use
Recommended Pattern: Write Script to File First
For complex multi-line scripts, especially when using shell_agent as executor:
# Step 1: Write the Python script to a file
cat > process_spreadsheet.py << 'EOF'
import openpyxl
from openpyxl import Workbook
# Your spreadsheet code here
wb = openpyxl.load_workbook('file.xlsx')
# ... operations ...
wb.save('output.xlsx')
print('Success')
EOF
# Step 2: Execute the script
python3 process_spreadsheet.py
Alternative Pattern: Inline Heredoc (Simple Scripts Only)
For short, simple scripts when NOT using shell_agent as the executor:
python3 << 'EOF'
import openpyxl
from openpyxl import Workbook
# Your spreadsheet code here
wb = openpyxl.load_workbook('file.xlsx')
# ... operations ...
wb.save('output.xlsx')
print('Success')
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.
- 4d ago First seen · 200 lines · 24 tokens per session scan A b841bf80397b
spreadsheet-python-file-exec is a skill published in the GitHub repository HKUDS/OpenSpace (7,544 stars, last pushed 26d ago), licensed MIT. It adds 24 tokens to every session and 1,345 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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