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 structured-document-creationgit 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/structured-document-creation)<a href="https://agentmods.dev/skills/hkuds/openspace/structured-document-creation"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/structured-document-creation.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 | $0.00021 | $0.01383 |
| Opus 5 | $0.00010 | $0.00691 |
| Sonnet 5 | $0.00004 | $0.00277 |
| Haiku 4.5 | $0.00002 | $0.00138 |
Grade A, and why
structured-document-creation 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structured Document Creation Workflow
This skill guides you through creating multiple audience-specific documents from a single reference source while maintaining consistency, proper formatting, and cross-references.
When to Use This Skill
Use this pattern when you need to:
- Create both internal and external-facing documents from the same source material
- Maintain consistent information across multiple documents
- Extract structured requirements (timelines, roles, steps, policies)
- Ensure proper cross-referencing between related documents
Step-by-Step Instructions
Step 1: Read and Analyze Reference Material
First, thoroughly read the reference document to understand the source content.
# Example: Read reference document
from docx import Document
def read_reference_doc(path):
doc = Document(path)
content = []
for para in doc.paragraphs:
content.append(para.text)
return '\n'.join(content)
reference_content = read_reference_doc('Reference_Document.docx')
Key actions:
- Identify all key sections, policies, and requirements
- Note any timelines, deadlines, or time-sensitive information
- Extract role definitions and responsibilities
- Identify process steps and workflows
- Flag any sensitive/internal-only information
Step 2: Extract Structured Requirements
Create a structured extraction of key information categories:
structured_requirements = {
'timelines': [], # Deadlines, timeframes, schedules
'roles': [], # Who is responsible for what
'steps': [], # Process steps in order
'policies': [], # Rules and guidelines
'contacts': [], # Points of contact
'internal_only': [] # Information not for external audiences
}
Extraction checklist:
- All dates and timeframes captured
- All roles and responsibilities identified
- All process steps documented in sequence
- All policies and rules extracted
- Sensitive information flagged for internal documents only
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 · 196 lines · 21 tokens per session scan A 0d2b9339332d
structured-document-creation is a skill published in the GitHub repository HKUDS/OpenSpace (7,544 stars, last pushed 26d ago), licensed MIT. It adds 21 tokens to every session and 1,383 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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