Ontology

sundial-org/awesome-openclaw-skills/skills/ontology

作者 sundial-orgb80cde2ef852無授權條款663 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫7 個月前更新

Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linking related objects, enforcing constraints, planning multi-step actions as graph transformations, or when skills need to share state. Trigger on "remember", "what do I know about", "link X to Y", "show dependencies", entity CRUD, or cross-skill data access.

包含腳本AI & Agents

AI 產生的概覽

維護由實體與關係組成的型別化知識圖譜，用於結構化代理記憶與跨技能狀態共享。

功能: 提供型別化詞彙表與約束系統，將實體（Person、Project、Task、Event、Document 等）及其屬性與關係儲存在 JSONL 圖形檔案中。隨附的 Python 指令碼支援建立、查詢、關聯與驗證實體，結構定義規則可強制必填欄位、列舉值與關係基數。它也說明如何把多步驟計畫建模為經過驗證的圖形轉換，並在技能之間共享狀態。
適用情境: 適用於代理需要持久化結構化記憶的情境，例如記住事實、查詢某個實體的已知資訊、關聯物件或追蹤相依關係。也適合多步驟規劃，以及需要透過共享圖形交換狀態的技能。
執行需求: 需要 Python 3 來執行 scripts/ontology.py，並需要可寫入的儲存位置，預設為 memory/ontology/graph.jsonl，可選用 schema.yaml。未提及憑證或網路存取；此技能附帶一個可執行指令碼與兩份參考文件。

Ontology

A typed vocabulary + constraint system for representing knowledge as a verifiable graph.

Core Concept

Everything is an entity with a type, properties, and relations to other entities. Every mutation is validated against type constraints before committing.

Entity: { id, type, properties, relations, created, updated }Relation: { from_id, relation_type, to_id, properties }

Entity: { id, type, properties, relations, created, updated }Relation: { from_id, relation_type, to_id, properties }

When to Use

Trigger	Action
"Remember that..."	Create/update entity
"What do I know about X?"	Query graph
"Link X to Y"	Create relation
"Show all tasks for project Z"	Graph traversal
"What depends on X?"	Dependency query
Planning multi-step work	Model as graph transformations
Skill needs shared state	Read/write ontology objects

Core Types

yaml

# Agents & PeoplePerson: { name, email?, phone?, notes? }Organization: { name, type?, members[] }
# WorkProject: { name, status, goals[], owner? }Task: { title, status, due?, priority?, assignee?, blockers[] }Goal: { description, target_date?, metrics[] }
# Time & PlaceEvent: { title, start, end?, location?, attendees[], recurrence? }Location: { name, address?, coordinates? }
# InformationDocument: { title, path?, url?, summary? }Message: { content, sender, recipients[], thread? }Thread: { subject, participants[], messages[] }Note: { content, tags[], refs[] }
# ResourcesAccount: { service, username, credential_ref? }Device: { name, type, identifiers[] }Credential: { service, secret_ref }  # Never store secrets directly
# MetaAction: { type, target, timestamp, outcome? }Policy: { scope, rule, enforcement }

# Agents & PeoplePerson: { name, email?, phone?, notes? }Organization: { name, type?, members[] }
# WorkProject: { name, status, goals[], owner? }Task: { title, status, due?, priority?, assignee?, blockers[] }Goal: { description, target_date?, metrics[] }
# Time & PlaceEvent: { title, start, end?, location?, attendees[], recurrence? }Location: { name, address?, coordinates? }
# InformationDocument: { title, path?, url?, summary? }Message: { content, sender, recipients[], thread? }Thread: { subject, participants[], messages[] }Note: { content, tags[], refs[] }
# ResourcesAccount: { service, username, credential_ref? }Device: { name, type, identifiers[] }Credential: { service, secret_ref }  # Never store secrets directly
# MetaAction: { type, target, timestamp, outcome? }Policy: { scope, rule, enforcement }

Storage

Default: memory/ontology/graph.jsonl

jsonl

{"op":"create","entity":{"id":"p_001","type":"Person","properties":{"name":"Alice"}}}{"op":"create","entity":{"id":"proj_001","type":"Project","properties":{"name":"Website Redesign","status":"active"}}}{"op":"relate","from":"proj_001","rel":"has_owner","to":"p_001"}

{"op":"create","entity":{"id":"p_001","type":"Person","properties":{"name":"Alice"}}}{"op":"create","entity":{"id":"proj_001","type":"Project","properties":{"name":"Website Redesign","status":"active"}}}{"op":"relate","from":"proj_001","rel":"has_owner","to":"p_001"}

Query via scripts or direct file ops. For complex graphs, migrate to SQLite.

Workflows

Create Entity

bash

python3 scripts/ontology.py create --type Person --props '{"name":"Alice","email":"[email protected]"}'

python3 scripts/ontology.py create --type Person --props '{"name":"Alice","email":"[email protected]"}'

Query

bash

python3 scripts/ontology.py query --type Task --where '{"status":"open"}'python3 scripts/ontology.py get --id task_001python3 scripts/ontology.py related --id proj_001 --rel has_task

python3 scripts/ontology.py query --type Task --where '{"status":"open"}'python3 scripts/ontology.py get --id task_001python3 scripts/ontology.py related --id proj_001 --rel has_task

Link Entities

Validate

Constraints

Define in memory/ontology/schema.yaml:

yaml

types:  Task:    required: [title, status]    status_enum: [open, in_progress, blocked, done]    Event:    required: [title, start]    validate: "end >= start if end exists"
  Credential:    required: [service, secret_ref]    forbidden_properties: [password, secret, token]  # Force indirection
relations:  has_owner:    from_types: [Project, Task]    to_types: [Person]    cardinality: many_to_one    blocks:    from_types: [Task]    to_types: [Task]    acyclic: true  # No circular dependencies

types:  Task:    required: [title, status]    status_enum: [open, in_progress, blocked, done]    Event:    required: [title, start]    validate: "end >= start if end exists"
  Credential:    required: [service, secret_ref]    forbidden_properties: [password, secret, token]  # Force indirection
relations:  has_owner:    from_types: [Project, Task]    to_types: [Person]    cardinality: many_to_one    blocks:    from_types: [Task]    to_types: [Task]    acyclic: true  # No circular dependencies

Skill Contract

Skills that use ontology should declare:

yaml

# In SKILL.md frontmatter or headerontology:  reads: [Task, Project, Person]  writes: [Task, Action]  preconditions:    - "Task.assignee must exist"  postconditions:    - "Created Task has status=open"

# In SKILL.md frontmatter or headerontology:  reads: [Task, Project, Person]  writes: [Task, Action]  preconditions:    - "Task.assignee must exist"  postconditions:    - "Created Task has status=open"

Planning as Graph Transformation

Model multi-step plans as a sequence of graph operations:

Plan: "Schedule team meeting and create follow-up tasks"
1. CREATE Event { title: "Team Sync", attendees: [p_001, p_002] }2. RELATE Event -> has_project -> proj_0013. CREATE Task { title: "Prepare agenda", assignee: p_001 }4. RELATE Task -> for_event -> event_0015. CREATE Task { title: "Send summary", assignee: p_001, blockers: [task_001] }

Plan: "Schedule team meeting and create follow-up tasks"
1. CREATE Event { title: "Team Sync", attendees: [p_001, p_002] }2. RELATE Event -> has_project -> proj_0013. CREATE Task { title: "Prepare agenda", assignee: p_001 }4. RELATE Task -> for_event -> event_0015. CREATE Task { title: "Send summary", assignee: p_001, blockers: [task_001] }

Each step is validated before execution. Rollback on constraint violation.

Integration Patterns

With Causal Inference

Log ontology mutations as causal actions:

python

# When creating/updating entities, also log to causal action logaction = {    "action": "create_entity",    "domain": "ontology",     "context": {"type": "Task", "project": "proj_001"},    "outcome": "created"}

# When creating/updating entities, also log to causal action logaction = {    "action": "create_entity",    "domain": "ontology",     "context": {"type": "Task", "project": "proj_001"},    "outcome": "created"}

Cross-Skill Communication

python

# Email skill creates commitmentcommitment = ontology.create("Commitment", {    "source_message": msg_id,    "description": "Send report by Friday",    "due": "2026-01-31"})
# Task skill picks it uptasks = ontology.query("Commitment", {"status": "pending"})for c in tasks:    ontology.create("Task", {        "title": c.description,        "due": c.due,        "source": c.id    })

# Email skill creates commitmentcommitment = ontology.create("Commitment", {    "source_message": msg_id,    "description": "Send report by Friday",    "due": "2026-01-31"})
# Task skill picks it uptasks = ontology.query("Commitment", {"status": "pending"})for c in tasks:    ontology.create("Task", {        "title": c.description,        "due": c.due,        "source": c.id    })

Quick Start

bash

# Initialize ontology storagemkdir -p memory/ontologytouch memory/ontology/graph.jsonl
# Create schema (optional but recommended)cat > memory/ontology/schema.yaml << 'EOF'types:  Task:    required: [title, status]  Project:    required: [name]  Person:    required: [name]EOF
# Start usingpython3 scripts/ontology.py create --type Person --props '{"name":"Alice"}'python3 scripts/ontology.py list --type Person

# Initialize ontology storagemkdir -p memory/ontologytouch memory/ontology/graph.jsonl
# Create schema (optional but recommended)cat > memory/ontology/schema.yaml << 'EOF'types:  Task:    required: [title, status]  Project:    required: [name]  Person:    required: [name]EOF
# Start usingpython3 scripts/ontology.py create --type Person --props '{"name":"Alice"}'python3 scripts/ontology.py list --type Person

References

references/schema.md — Full type definitions and constraint patterns
references/queries.md — Query language and traversal examples

來源與署名

來源：sundial-org/awesome-openclaw-skills位於skills/ontology提交b80cde2

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檢舉或申請下架

Ontology

Ontology

Core Concept

When to Use

Core Types

Storage

Workflows

Create Entity

Query

Link Entities

Validate

Constraints

Skill Contract

Planning as Graph Transformation

Integration Patterns

With Causal Inference

Cross-Skill Communication

Quick Start

References

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