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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/HKUDS/OpenSpacenpx agentmods add skills/hkuds/openspace/shell-agent-file-workflowWrote 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/shell-agent-file-workflow)<a href="https://agentmods.dev/skills/hkuds/openspace/shell-agent-file-workflow"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/shell-agent-file-workflow/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.
<a href="https://agentmods.dev/skills/hkuds/openspace/shell-agent-file-workflow"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/shell-agent-file-workflow.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00023 | $0.00730 |
| Opus 5 | $0.00012 | $0.00365 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
shell-agent-file-workflow 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 5d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shell Agent File Generation Workflow
When direct document or file generation approaches fail, delegate the task to shell_agent which can autonomously write code, execute it, and retry on errors. Generated files may appear in nested workspace directories.
When to Use
- Direct file generation tools or
create_filefunctions fail for complex formats - Complex file creation requiring multiple steps, libraries, or error recovery
- When you need an autonomous agent to figure out how to accomplish a goal
- File generation that requires iteration and automatic error fixing
Workflow Steps
Step 1: Delegate File Generation to shell_agent
Use shell_agent with a clear, specific task description:
shell_agent(task="Create a [file type] with [specific content/structure requirements]")
The agent will:
- Decide whether to use Python or Bash
- Write and execute code
- Inspect output and iterate
- Automatically retry and fix errors (up to several rounds)
Step 2: Locate Generated Files
Files may be created in nested directories within the workspace. Use find to locate them:
find . -name "*.extension" -type f
For multiple file types:
find . -type f \( -name "*.pptx" -o -name "*.docx" -o -name "*.pdf" \)
For recently modified files (last 10 minutes):
find . -name "*.extension" -type f -mmin -10
Step 3: Copy Files to Working Directory
Once located, copy the file to your working directory:
cp /path/to/found/file.extension ./
Example
Creating a PowerPoint Presentation
# Step 1: Delegate to shell_agent
shell_agent(task="Create a 10-slide PowerPoint presentation covering: topic A, topic B, topic C")
# Step 2: Find the generated file
find . -name "*.pptx" -type f
# Output might show: ./workspace/nested/path/presentation.pptx
# Step 3: Copy to working directory
cp ./workspace/nested/path/presentation.pptx ./
Creating a PDF Report
# Step 1: Delegate generation
shell_agent(task="Generate a PDF report with charts and tables from the provided data")
# Step 2: Locate output
find . -name "*.pdf" -type f -mmin -5
# Step 3: Retrieve file
cp ./generated/reports/output.pdf ./
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.
- 5d ago First seen · 103 lines · 23 tokens per session scan A de38b5ec4274
shell-agent-file-workflow is a skill published in the GitHub repository HKUDS/OpenSpace (7,544 stars, last pushed 27d ago), licensed MIT. It adds 23 tokens to every session and 730 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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