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 agentmods add skills/hkuds/openspace/regulatory-research-fallbacknpx skills add HKUDS/OpenSpace --skill regulatory-research-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/regulatory-research-fallback)<a href="https://agentmods.dev/skills/hkuds/openspace/regulatory-research-fallback"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/regulatory-research-fallback.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00020 | $0.00795 |
| Opus 5 | $0.00010 | $0.00398 |
| Sonnet 5 | $0.00004 | $0.00159 |
| Haiku 4.5 | $0.00002 | $0.00080 |
Grade A, and why
regulatory-research-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 2d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regulatory Research Fallback Workflow
This skill provides a systematic approach to gathering regulatory/compliance information when primary web extraction tools fail on government or regulatory website URLs.
When to Use This Skill
read_webpagereturns "unknown error" on .gov or regulatory PDF URLssearch_webfails to retrieve current regulatory information- You need to create compliance checklists or regulatory documentation
- Primary sources are inaccessible but the task must be completed
Step-by-Step Procedure
Step 1: Attempt Primary Source Extraction
First, try standard web extraction tools:
1. Use read_webpage on the regulatory URL
2. Use search_web for supplementary regulatory information
3. Document which tools failed and with what errors
Step 2: Activate Fallback - Shell Agent Research
When primary tools fail, delegate to shell_agent for secondary research:
Task: "Research [TOPIC] compliance requirements using available system tools.
Gather information from alternative sources including:
- State/federal regulatory summaries
- Industry compliance guides
- Professional association resources
Focus on actionable checklist items for [SPECIFIC REQUIREMENT]"
Example shell_agent task for pharmacy compliance:
"Research pharmacy compliance requirements for [state]. Gather information
about licensing, storage, dispensing, and documentation requirements from
available sources. Create structured notes on mandatory compliance areas."
Step 3: Apply Domain Knowledge
When sources remain inaccessible, use established domain knowledge:
For pharmacy compliance, standard areas include:
- Licensing and registration requirements
- Controlled substance handling
- Prescription record-keeping
- Storage and security protocols
- Patient counseling requirements
- Continuing education obligations
Step 4: Create Documentation with Confidence Levels
Structure output with clear sourcing transparency:
## [Requirement Area]
**Status**: Based on standard regulatory framework (primary sources inaccessible)
**Key Requirements**:
- [Item 1] - Standard industry requirement
- [Item 2] - Common regulatory expectation
- [Item 3] - Best practice guideline
**Note**: Verify with [specific agency] for jurisdiction-specific requirements
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.
- 2d ago First seen · 134 lines · 20 tokens per session scan A 5f3733983e91
regulatory-research-fallback is a skill published in the GitHub repository HKUDS/OpenSpace (7,506 stars, last pushed 24d ago), licensed MIT. It adds 20 tokens to every session and 795 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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