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 document-gen-fallback-enhanced-enhanced-96865fgit 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/document-gen-fallback-enhanced-enhanced-96865f)<a href="https://agentmods.dev/skills/hkuds/openspace/document-gen-fallback-enhanced-enhanced-96865f"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/document-gen-fallback-enhanced-enhanced-96865f/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/document-gen-fallback-enhanced-enhanced-96865f"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/document-gen-fallback-enhanced-enhanced-96865f.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 | $0.00021 | $0.03267 |
| Opus 5 | $0.00010 | $0.01633 |
| Sonnet 5 | $0.00004 | $0.00653 |
| Haiku 4.5 | $0.00002 | $0.00327 |
Grade A, and why
document-gen-resilient 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 10d 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 — 404 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resilient Document Generation Workflow
When to Use
Use this skill when document generation tasks encounter errors or when you need reliable multi-format output:
shell_agentreturns unknown or unclear errors on document generation- Generating documents in multiple formats (e.g.,
.docx,.pdf,.html) - PDF generation fails due to LaTeX encoding or missing dependencies
- You need to handle special characters, symbols, or non-ASCII text safely
- Previous document generation attempts have failed
Core Technique
Instead of delegating the entire document generation to shell_agent, manually split the workflow into discrete, observable steps with built-in fallbacks:
- Tool availability check → Verify pandoc and PDF engines are available
- Content creation → Use
write_fileto create source document (Markdown) - Unicode assessment → Determine if sanitization is needed based on target format
- Format conversion → Try primary method, fall back to alternatives on failure
- Verification → Check output files exist and are valid
⚠️ Format-Specific Unicode Guidance
Critical: Different formats handle Unicode differently. Plan accordingly:
| Format | Unicode Support | Sanitization Needed? | Recommended Engine |
|---|---|---|---|
.docx |
Excellent | No | pandoc (default) |
.html |
Excellent | No | pandoc (default) |
.pdf (pdflatex) |
Limited | Yes | pandoc + sanitization |
.pdf (xelatex) |
Good | Rarely | pandoc --pdf-engine=xelatex |
.pdf (wkhtmltopdf) |
Good | Rarely | pandoc --pdf-engine=wkhtmltopdf |
.pdf (Python) |
Excellent | No | fpdf2 or reportlab |
Step-by-Step Workflow
Step 0: Check Tool Availability
Before starting, verify which tools are available:
run_shell
command: which pandoc && echo "PANDOC: OK" || echo "PANDOC: MISSING"
run_shell
command: which pdflatex && echo "PDFLATEX: OK" || echo "PDFLATEX: MISSING"
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.
- 10d ago First seen · 404 lines · 21 tokens per session scan A b45e65f4629c
document-gen-resilient is a skill published in the GitHub repository HKUDS/OpenSpace (7,552 stars, last pushed 28d ago), licensed MIT. It adds 21 tokens to every session and 3,267 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 2026-08-30.
Other skills, from other repositories
pydicom
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foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
parse-document
Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.
meta-web-to-pdf-briefing
Render a topic into a distributable PDF briefing in three steps: web search → bullet summary → styled PDF. Trigger when the user asks for a PDF briefing on a single topic.
chat-complex-documents
Chat with and search your complex documents — ask questions, extract tables and fields, and get answers grounded in the source. Connects the hosted Unstructured Transform MCP server to parse, structure, and enrich PDFs, Word/Excel/PowerPoint, images, scanned files, emails, and 60+ other formats into clean, AI-ready…