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Agent Skill · 开发

obsidian-ontology-sync(Obsidian ontology sync 开发)

obsidian-ontology-sync 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

obsidian-ontology-sync 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 143。

总安装 227,862周安装 9,688GitHub Stars 15下载 79,829核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:obsidian-ontology-sync(Obsidian ontology sync 开发)
来源仓库:https://github.com/parthpandya1729/obsidian-ontology-sync
安装命令:
openclaw skills install obsidian-ontology-sync
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install obsidian-ontology-sync

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

实现 PKM 笔记与机器可读本体的双向同步。自动提取实体关系构建知识图谱。obsidian-ontology-sync 属于开发类 Skill,可作为该场景下的辅助能力补充。使用 openclaw skills install obsidian-ontology-sync 安装。

需确认图数据库接口与 schema 兼容性。建议先定义核心实体类型再启动同步。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install obsidian-ontology-sync;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

obsidian-ontology-sync 怎么安装?

在终端执行 openclaw skills install obsidian-ontology-sync。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

obsidian-ontology-sync 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

obsidian-ontology-sync 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

obsidian-ontology-sync 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

obsidian-ontology-sync 用的人多吗?

公开数据是累计安装 227,862 次,近一周安装 9,688 次,下载 79,829 次,GitHub 15 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

obsidian-ontology-sync 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
obsidian-ontology-sync

Obsidian ontology sync 开发 · 本页

227,86215只读MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
obsidian-ontology-sync
description
Bidirectional sync between Obsidian PKM (human-friendly notes) and structured ontology (machine-queryable graph). Automatically extracts entities and relationships from markdown, maintains ontology graph, and provides feedback to improve note structure. Run sync every few hours via cron.
metadata

Obsidian-Ontology Sync

Philosophy: Obsidian is PRIMARY (human writes natural notes) → Ontology is DERIVED (machine extracts structure) → Feedback loop improves both

Core Concept

Obsidian Notes (Markdown)
    ↓ Extract (every 3 hours)
Ontology Graph (Structured)
    ↓ Query & Analyze
Insights & Suggestions
    ↓ Feedback
Improved Note Templates

When to Use

SituationAction
After creating/updating contactsRun sync to extract entities
Before business queriesSync then query ontology
Weekly reviewSync + analyze + get suggestions
New project setupExtract entities + suggest structure
Team status trackingSync daily-status → ontology → analytics

What Gets Extracted

From Contact Notes (references/contacts/*.md)

Extracts:

  • Person entity (name, email, phone)
  • works_at → Organization
  • met_at → Event
  • assigned_to → Project (if mentioned)
  • status → (prospect, warm_lead, client, etc.)

Example:

# Alice Johnson

**Email:** alice@company.com
**Company:** Acme Corp
**Met At:** Tech Conference 2026
**Projects:** Project Alpha

## Notes
Great developer, responsive communication.

Becomes:

{
  "entity": {
    "id": "person_alice_johnson",
    "type": "Person",
    "properties": {
      "name": "Alice Johnson",
      "email": "alice@company.com",
      "notes": "Great developer, responsive communication"
    }
  },
  "relations": [
    {"from": "person_alice_johnson", "rel": "works_at", "to": "org_acme"},
    {"from": "person_alice_johnson", "rel": "met_at", "to": "event_tech_conference_2026"},
    {"from": "person_alice_johnson", "rel": "assigned_to", "to": "project_alpha"}
  ]
}

From Client Notes (references/clients/*.md)

Extracts:

  • Organization entity
  • has_contract_value → number
  • projects → Project entities
  • primary_contact → Person

From Team Notes (references/team/*.md)

Extracts:

  • Person entity
  • works_for → Organization
  • assigned_to → Project[]
  • reports_to → Person
  • response_pattern → (proactive, reactive, non-responsive)

From Daily Status (daily-status/YYYY-MM-DD/*.md)

Extracts:

  • response_time property on Person
  • status_update → Event
  • blockers → Issue entities
  • behavioral_pattern tracking

From Project Notes (projects/*.md)

Extracts:

  • Project entity
  • for_client → Organization
  • team → Person[]
  • status, value, deadline

Sync Process

1. Extract Phase (Markdown → Ontology)

# Run extraction
python3 skills/obsidian-ontology-sync/scripts/sync.py extract

# What it does:
# 1. Scan configured Obsidian directories
# 2. Parse markdown frontmatter + content
# 3. Extract entities (Person, Project, Organization, etc.)
# 4. Extract relationships (works_at, assigned_to, etc.)
# 5. Write to ontology using append-only operations

Detection Rules:

# Contact files
if file.startswith("references/contacts/"):
    entity_type = "Person"
    extract_email_from_content()
    extract_company_from_property("Company:")
    extract_projects_from_links([[Project]])
    
# Client files
if file.startswith("references/clients/"):
    entity_type = "Organization"
    extract_contract_value()
    extract_projects()
    
# Team files
if file.startswith("references/team/"):
    entity_type = "Person"
    role = "team_member"
    extract_assignments()
    extract_response_patterns()

2. Analysis Phase (Ontology → Insights)

# Run analytics
python3 skills/obsidian-ontology-sync/scripts/sync.py analyze

# Generates insights like:
# - "3 team members have no assigned projects"
# - "Contact 'John Doe' missing email address"
# - "Project 'X' has 5 people but no client linked"
# - "10 contacts from AI Summit not linked to follow-up tasks"

3. Feedback Phase (Insights → Improve PKM)

# Get suggestions
python3 skills/obsidian-ontology-sync/scripts/sync.py feedback

# Creates:
# - Missing property suggestions
# - Broken link reports
# - Relationship suggestions
# - Template improvements

Example Feedback:

# Sync Feedback - 2026-02-27

## Missing Information (10 items)
- [ ] `Alice Johnson` missing phone number
- [ ] `Bob` missing email in team file
- [ ] Project `Project Alpha` missing deadline

## Suggested Links (5 items)
- [ ] Link `Jane Doe` (TechHub) to organization `TechHub`
- [ ] Link `Eve` to project (found in daily-status but not in team file)

## Relationship Insights
- `Project Alpha` team: Alice, Carol, David (extracted from daily-status)
- Suggest updating project file with team assignments

## Template Suggestions
- Add `Projects: [[]]` field to contact template
- Add `Response Pattern:` field to team template

Configuration

config.yaml

# /root/life/pkm/ontology-sync/config.yaml

obsidian:
  vault_path: /root/life/pkm
  
  # What to sync
  sources:
    contacts:
      path: references/contacts
      entity_type: Person
      extract:
        - email_from_content
        - company_from_property
        - projects_from_links
    
    clients:
      path: references/clients
      entity_type: Organization
      extract:
        - contract_value
        - projects
        - contacts
    
    team:
      path: references/team
      entity_type: Person
      role: team_member
      extract:
        - assignments
        - response_patterns
        - reports_to
    
    daily_status:
      path: daily-status
      extract:
        - response_times
        - behavioral_patterns
        - blockers

ontology:
  storage_path: /root/life/pkm/memory/ontology
  format: jsonl  # or sqlite for scale
  
  # Entity types to track
  entities:
    - Person
    - Organization
    - Project
    - Event
    - Task
  
  # Relationships to extract
  relationships:
    - works_at
    - assigned_to
    - met_at
    - for_client
    - reports_to
    - has_task
    - blocks

feedback:
  output_path: /root/life/pkm/ontology-sync/feedback
  generate_reports: true
  suggest_templates: true
  highlight_missing: true

schedule:
  # Run via cron every 3 hours
  sync_interval: "0 */3 * * *"
  analyze_daily: "0 9 * * *"  # 9 AM daily
  feedback_weekly: "0 10 * * MON"  # Monday 10 AM

Scheduled Sync (Cron Integration)

Setup Automatic Sync

# Add to OpenClaw cron
python3 skills/obsidian-ontology-sync/scripts/setup-cron.py

# Or manually via cron tool
cron add \
  --schedule "0 */3 * * *" \
  --task "python3 skills/obsidian-ontology-sync/scripts/sync.py extract" \
  --label "Obsidian → Ontology Sync"

Cron Jobs Created:

  1. Every 3 hours: Extract entities from Obsidian → Update ontology
  2. Daily 9 AM: Run analytics and generate insights
  3. Weekly Monday 10 AM: Generate feedback report + template suggestions

Queries (Using Ontology)

Once synced, you can query:

# All team members on high-value projects
python3 skills/ontology/scripts/ontology.py query \
  --type Person \
  --where '{"role":"team_member"}' \
  --related assigned_to \
  --filter '{"type":"Project","value__gt":400000}'

# Contacts from specific event not yet followed up
python3 skills/ontology/scripts/ontology.py query \
  --type Person \
  --where '{"met_at":"event_tech_conference_2026"}' \
  --missing has_task

# Team response patterns
python3 skills/ontology/scripts/ontology.py query \
  --type Person \
  --where '{"role":"team_member"}' \
  --aggregate response_pattern

# Projects by client
python3 skills/ontology/scripts/ontology.py query \
  --type Project \
  --group-by for_client \
  --count

Feedback Loop Examples

Example 1: Missing Email Detection

Ontology finds: Person entity with no email property

Feedback generated:

## Missing Contact Information

The following team members are missing email addresses:

- [ ] Bob (`references/team/Bob.md`)
- [ ] Lucky (`references/team/Lucky.md`)

**Suggestion:** Add email field to team member template:
\`\`\`markdown
**Email:** 
\`\`\`

Example 2: Broken Project Links

Ontology finds: Person assigned_to Project that doesn't exist

Feedback generated:

## Broken Project References

Found references to projects that don't have dedicated files:

- [ ] "Project Epsilon" mentioned in team files but no `projects/Project Epsilon.md`
- [ ] "Project Delta Tata DT" assigned but no project file

**Suggestion:** Create project files with template

Example 3: Relationship Discovery

Ontology finds: Multiple people working at same company

Feedback generated:

## Suggested Company Grouping

Found 3 contacts at "TechHub":
- Jane Doe
- [2 others from daily-status mentions]

**Suggestion:** Create `references/clients/TechHub.md` and link contacts

Integration with Daily Workflow

Morning Routine (9 AM)

# Cron runs analysis
# Generates daily-insights.md with:
- Response rate from yesterday's status requests
- Projects needing attention (blockers mentioned)
- Contacts to follow up (met > 3 days ago, no task)

Weekly Review (Monday 10 AM)

# Cron generates weekly feedback
# Creates suggestions for:
- Missing information to fill in
- Broken links to fix
- New templates to adopt
- Relationship insights

On-Demand Queries

# Before a meeting
"Show me all interactions with Client X"

# Resource planning
"Which team members are on <3 projects?"

# Sales pipeline
"Contacts met at conferences in last 30 days without follow-up"

Benefits

✅ For You

  1. Zero Extra Work: Just keep writing normal Obsidian notes
  2. Automatic Structure: Ontology extracted automatically
  3. Powerful Queries: Find patterns across all your data
  4. Quality Improvement: Feedback loop catches missing info
  5. No Double Entry: Single source of truth (Obsidian)

✅ For Team Management

  • Track who's on which project (auto-extracted)
  • Monitor response patterns (from daily-status)
  • Identify unbalanced workloads
  • Find blockers across projects

✅ For Sales/BD

  • Track contact network (who you met, where, when)
  • Follow-up reminders (contacted >7 days ago)
  • Relationship mapping (who knows who)
  • Pipeline insights (prospects → warm → clients)

✅ For Finance

  • Project valuations (extracted from client notes)
  • Team cost allocation (people → projects → revenue)
  • Revenue forecasting (active projects × value)

File Structure After Sync

/root/life/pkm/
├── references/
│   ├── contacts/          # Source notes (you write these)
│   ├── clients/           # Source notes
│   └── team/              # Source notes
├── daily-status/          # Source notes
├── projects/              # Source notes
│
├── memory/ontology/       # Generated ontology
│   ├── graph.jsonl        # Entity/relation storage
│   └── schema.yaml        # Type definitions
│
└── ontology-sync/         # Sync outputs
    ├── config.yaml        # Your config
    ├── feedback/
    │   ├── daily-insights.md
    │   ├── weekly-feedback.md
    │   └── suggestions.md
    └── logs/
        └── sync-YYYY-MM-DD.log

Advanced: Bidirectional Sync

Future capability:

Update Obsidian notes FROM ontology insights:

# Automatically add missing fields
python3 skills/obsidian-ontology-sync/scripts/sync.py apply-feedback

# What it does:
# - Adds missing email field to contact notes
# - Creates suggested project files
# - Links related entities
# - Updates frontmatter

Safety: Always creates backup before modifying files.

Comparison with Alternatives

ApproachProsCons
Manual ontologyFull controlToo much work, falls behind
Obsidian onlySimpleNo structured queries
Ontology onlyPowerful queriesNot human-friendly
This skillBest of bothInitial setup needed

Getting Started

1. Install Dependencies

# Already have ontology skill installed
clawhub install obsidian  # If not already installed

2. Create Config

python3 skills/obsidian-ontology-sync/scripts/init.py

# Creates:
# - config.yaml with your vault path
# - ontology directory structure
# - cron jobs

3. Run First Sync

# Manual first sync to test
python3 skills/obsidian-ontology-sync/scripts/sync.py extract --dry-run

# See what would be extracted
# Review, then run for real:
python3 skills/obsidian-ontology-sync/scripts/sync.py extract

4. Enable Automatic Sync

python3 skills/obsidian-ontology-sync/scripts/setup-cron.py

# Confirms cron jobs:
# ✓ Sync every 3 hours
# ✓ Daily analysis at 9 AM
# ✓ Weekly feedback Monday 10 AM

5. Query Your Data

# Try some queries
python3 skills/obsidian-ontology-sync/scripts/query.py "team members on high value projects"

Troubleshooting

Extraction Issues

# Dry run to see what would be extracted
python3 skills/obsidian-ontology-sync/scripts/sync.py extract --dry-run --verbose

# Check specific file
python3 skills/obsidian-ontology-sync/scripts/debug.py \
  --file references/contacts/Alice.md

Query Not Finding Data

# Check what's in ontology
python3 skills/ontology/scripts/ontology.py query --type Person

# Verify sync ran
cat /root/life/pkm/ontology-sync/logs/sync-latest.log

Feedback Not Generated

# Manually run analysis
python3 skills/obsidian-ontology-sync/scripts/sync.py analyze
python3 skills/obsidian-ontology-sync/scripts/sync.py feedback

Version History

  • 1.0.0 (2026-02-27) - Initial version with extraction, analysis, feedback loop

Author: Built for team management, contact tracking, and business intelligence at scale License: MIT Tags: obsidian, ontology, knowledge-graph, pkm, automation, sync

平台分布

OpenClaw

92.46%
按下载量换算73,810

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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