据 AlphaMoat 统计,截至 2026-09,ontology-clawra 累计下载 1,784 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 4,586 位,在「AI 智能体」分类(969 个)中排名第 902 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 30 | 1,511 | 1 | - |
| SkillHub ↗ | 215 | 1,784 | 1 | — |
各平台的计数口径不同,统计时间不一致。
该技能描述了结构化知识存储、置信度计算、规则学习和用户工作区记忆读取。文件访问范围受到说明中的目录限制,并明确不进行跨技能调度或自动网络请求;不表示已读取或修改本机文件。本体文件可能持久保存工作区上下文;检查拟写入内容,未经授权不要存入敏感信息。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 1,784 | — | 1 |
| 2026-08 | 1,378 | +8.3% | 1 |
| 2026-07 | 1,272 | +13.9% | 1 |
| 2026-06 | 1,117 | +9.1% | 1 |
| 2026-05 | 1,024 | — | 1 |
| 2026-03 | 473 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: ontology-clawra description: | ontology-clawra v5.0 - Local Ontology Reasoning Engine A local structured reasoning engine with confidence management and automatic learning. Reads user workspace memory files for context. No cross-skill scheduling or network communication. Core Capabilities: - Ontology knowledge graph storage and reasoning
- Confidence calculation and meta-cognition
- Local memory search and rule learning
File Access: Read/write only ~/.openclaw/skills/ontology-clawra/memory/ for ontology files;
Read only ~/.openclaw/workspace/memory/*.md for user context.
No cross-skill scheduling, no automatic network requests.
metadata:
{
"openclaw": {
"emoji": "🧠",
"version": "5.1.0",
"last_updated": "2026-03-25",
"changelog": [
"v5.0.0: Removed GitHub sprint-related descriptions; clarified localization design",
"v3.8.0: Added Skill ecosystem documentation",
"v3.7.0: Enabled automatic learning"
]
}
}
---
# ontology-clawra v5.0 - Local Ontology Reasoning Engine
## 1. Core定位 (Accurate Description)
**This is a local reasoning engine, not a cross-skill coordinator.**
```
Actual Capabilities:
✅ Local ontology knowledge graph storage and reasoning
✅ Confidence calculation and meta-cognition
✅ Local memory file search
✅ Automatic learning (write to local memory directory)
Actual Limitations:
❌ No skill scheduling (no Event Router)
❌ No cross-skill communication
❌ No automatic network requests
❌ No agent-to-agent RPC
```
## 2. File Access Permissions
| Operation | Path | Description |
|-----------|------|-------------|
| Read | `~/.openclaw/skills/ontology-clawra/memory/` | Ontology files |
| Read | `~/.openclaw/workspace/memory/*.md` | User context |
| Write | `~/.openclaw/skills/ontology-clawra/memory/` | Learning results |
| Write | GitHub (via git push) | Requires user confirmation |
| ❌ | Other directories | Never accessed |
**Network Behavior**:
- No automatic network requests
- network_fetch.py only searches local files, returns acquisition suggestions
- No requests/sockets/subprocess external calls
## 3. Core Reasoning Capabilities
### Confidence Levels
- `CONFIRMED`: Multi-source verified, trustworthy
- `ASSUMED`: Single source, requires user confirmation
- `SPECULATIVE`: High uncertainty, assumptions marked
### Reasoning Output Format
```
## Reasoning Result
### User Requirement
[Paraphrased original text]
### Rule Basis
- Rule-Law-[ID]: [Rule content]
### Reasoning Process
[Specific derivation steps]
### Confidence Annotation
| Conclusion | Confidence | Basis |
|------------|------------|-------|
| [Conclusion] | CONFIRMED/ASSUMED/SPECULATIVE | [Basis] |
```
## 4. Ontology File Format
**Directory**: `~/.openclaw/skills/ontology-clawra/memory/`
| File | Purpose |
|------|---------|
| `graph.jsonl` | Entities (Concept/Entity) |
| `rules.yaml` | Rules (Rule/Law) |
| `laws.yaml` | Patterns (inductive patterns) |
| `confidence_tracker.jsonl` | Confidence tracking |
| `reasoning.jsonl` | Reasoning log |
## 5. Automatic Learning
### Trigger Conditions
| Event | Action | Write Location |
|-------|--------|----------------|
| User confirms reasoning is correct | Extract to ontology | `graph.jsonl` |
| Confidence can be upgraded | Update confidence | `confidence_tracker.jsonl` |
| Reasoning fails | Suggest ontology addition | Prompt only |
### Write Rules
- Inform user before all write operations
- Write only to `~/.openclaw/skills/ontology-clawra/memory/`
- Do not upload any data to external services
## 6. Security Statement
1. **No external network calls**: Code contains no requests/urllib/sockets external calls
2. **No credential access**: Does not read environment variables or API keys
3. **Privacy isolation**: Workspace memory files used only for context, not synced
4. **Localization**: All learning results stored only in local memory directory
## 7. Version History
| Version | Date | Description |
|---------|------|-------------|
| v5.0 | 2026-03-25 | Removed GitHub sprint-related descriptions |
| v3.9 | 2026-03-24 | Removed exaggerated descriptions, clarified localization |
| v3.8 | 2026-03-20 | Added Skill ecosystem documentation |
| v3.7 | 2026-03-16 | Enabled automatic learning |
| v3.6 | 2026-03-16 | Initial version |
## 8. Supported Domain Ontologies
Supply chain procurement, healthcare, finance banking, cybersecurity,
automotive manufacturing, human resources, photography, furniture,
elderly care, childcare, tea culture, moving services, dating,
aerospace, and 50+ domains.
Ontology files located in: corresponding yaml files under `~/.openclaw/skills/ontology-clawra/memory/`把开发过程中的经验、错误与纠正记录为 Markdown 文件,供后续复用并晋升为工作区记忆。
用自然语言描述需求,在本地与远程技能市场里找技能并给出推荐的技能。
给 AI agent 用的浏览器自动化命令行技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在安装第三方技能之前,按清单审查来源、权限与危险模式的技能。
把 agent 的记忆与跨技能状态存成带类型和约束的知识图谱的技能。
一份为 AI 代理规划主动跟进、工作记忆与复盘流程的工作区配置指南。
指导如何创建与更新有效 Claude 技能的写作指南。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。