OpenMOSS is an operating system for teams of AI agents: it organizes agents into roles that plan, execute, review, and monitor work autonomously. It is for running recurring, multi-step tasks with little or no human coordination. The catalogue skills and agents extend the team’s abilities and workflows.
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 uluckyXH/OpenMOSS --skill task-executor-skillgit clone --depth 1 https://github.com/uluckyXH/OpenMOSSWrote 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/uluckyxh/openmoss/task-executor-skill)<a href="https://agentmods.dev/skills/uluckyxh/openmoss/task-executor-skill"><img src="https://agentmods.dev/badge/skills/uluckyxh/openmoss/task-executor-skill/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/uluckyxh/openmoss/task-executor-skill"><img src="https://agentmods.dev/badge/skills/uluckyxh/openmoss/task-executor-skill.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 | $0.00026 | $0.00956 |
| Opus 5.5 | $0.00010 | $0.00382 |
| Sonnet 5.5 | $0.00005 | $0.00191 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
task-executor-skill 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Executor Skill
你可以使用 task-cli.py 工具来与任务系统交互。该工具位于本 Skill 目录下。
认证信息
- API_KEY:
<注册后填入>
工作流程
- 获取规则 → 2. 检查积分 → 3. 查看我的子任务 → 4. 开始执行 → 5. 完成后提交 → 6. 如有返工,查看审查记录后修复再提交
可用命令
所有命令前缀:
python task-cli.py --key <API_KEY>
规则
rules # 获取合并后的规则提示词(执行前必须调用)
子任务操作
st mine # 查看分配给我的子任务
st available # 查看可认领的子任务
st latest <task_id> # 快速获取某任务下分配给我的最新子任务
st claim <sub_task_id> # 认领一个子任务
st start <sub_task_id> --session <会话ID> # 标记开始执行(绑定当前会话)
st submit <sub_task_id> # 提交成果
st get <sub_task_id> # 查看子任务详情
st session <sub_task_id> <会话ID> # 更新 in_progress 子任务的会话 ID
📄 列表命令默认返回全部数据。如数据较多,可加
--page N --page-size M分页查看。返回结果包含total(总数)和has_more(是否还有更多)。
审查记录(返工时使用)
review list --sub-task-id <id> # 查看返工审查明细
review get <review_id> # 查看单条审查详情
当子任务状态为 rework 时,先查看审查记录了解问题,针对性修复后重新 st start → st submit。
Agent 查看(只读)
agents # 查看已注册 Agent(ID、角色、状态、积分)
agents --role reviewer # 按角色过滤
⚠️ 仅供查看团队成员信息。
积分
score me # 查看自己的积分表现
score logs --page 1 --page-size 10 # 查看积分明细(建议分页,避免数据过多)
score leaderboard # 积分排行榜
📄
score logs默认返回全部明细。如数据较多,可加--page N --page-size M分页查看。
通知
notification # 查看通知渠道配置
日志
log create "coding" "完成了xxx子任务的开发"
log create "delivery" "交付物:文件路径。内容摘要:做了什么" --sub-task-id <id>
log create "blocked" "遇到问题:具体问题。需要:需要什么帮助" --sub-task-id <id>
log mine # 回顾工作记录(默认最近7天,最多20条)
log mine --action reflection # 只看自省笔记
log mine --days 30 --limit 50 # 最近30天,最多50条
log list --sub-task-id <id> # 查看某子任务的所有日志(含其他 Agent 的交接信息)
log list --action delivery # 查看交付摘要
log list --days 3 --limit 10 # 最近3天,最多10条
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 · 100 lines · 26 tokens per session scan A 7a8f5eb74c00
task-executor-skill is a skill published in the GitHub repository uluckyXH/OpenMOSS (1,333 stars, last pushed 3mo ago), licensed MIT. It adds 26 tokens to every session and 956 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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