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 deliverable-completiongit 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/deliverable-completion)<a href="https://agentmods.dev/skills/hkuds/openspace/deliverable-completion"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/deliverable-completion/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/deliverable-completion"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/deliverable-completion.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 | $0.00025 | $0.00654 |
| Opus 5.5 | $0.00010 | $0.00262 |
| Sonnet 5.5 | $0.00005 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
deliverable-completion 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 1mo 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deliverable Completion Protocol
Purpose
This skill addresses a common misconception during document and file creation tasks: agents sometimes search for or attempt to use a submit_work, finalize, or similar tool after creating the deliverable. No such step is required. Task completion is achieved when the file is successfully created with the required content.
Core Principle
File creation = Task completion
When a task requests you to create a document, report, script, or any file-based deliverable, the task is complete once:
- The file has been written to disk
- The file contains the required content
- The file is in the correct format and location
There is no additional submission, finalization, or confirmation step needed.
Execution Workflow
Step 1: Create the Deliverable
Use the appropriate file creation method for your task:
# For programmatic file creation
with open('deliverable.docx', 'wb') as f:
f.write(document_content)
# For shell-based creation
echo "content" > output.txt
Or use available tools like write_file, create_file, etc.
Step 2: Verify Creation
Confirm the file exists and contains expected content:
ls -la deliverable.docx
# or
cat output.txt
Step 3: Declare Completion
Once verification passes, the task is complete. Do not:
- Search for a
submit_worktool - Look for a
finalize_taskfunction - Attempt to "upload" or "submit" the file elsewhere
- Add extra confirmation steps
Simply report that the deliverable has been created successfully.
Common Mistakes to Avoid
| ❌ Incorrect | ✅ Correct |
|---|---|
| Creating file, then searching for submit tool | Creating file, verifying, declaring done |
| Assuming a finalization API exists | Treating file creation as the final step |
| Adding unnecessary confirmation steps | Completing after successful write |
Example Task Flow
Task: "Create a negotiation strategy document covering BATNA, ZOPA, and timeline."
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.
- 1mo ago First seen · 93 lines · 25 tokens per session scan A ad96e96b3908
deliverable-completion is a skill published in the GitHub repository HKUDS/OpenSpace (7,760 stars, last pushed 2mo ago), licensed MIT. It adds 25 tokens to every session and 654 once invoked, about $0.0001 per session on Opus 5.5. 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.
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