AgentSkillsCN

state

为某一特定领域创建当前世界状态的表征模型。适用于建模系统状态、构建世界模型、捕捉实体间的关系,或建立基准快照。

SKILL.md
--- frontmatter
name: state
description: Create representation of current world state for a domain. Use when modeling system state, building world models, capturing entity relationships, or establishing baseline snapshots.
argument-hint: "[scope] [schema] [timestamp]"
disable-model-invocation: false
user-invocable: true
allowed-tools: Read, Grep
context: fork
agent: explore
layer: MODEL

Intent

Create a structured representation of the current state of a domain, system, or entity. This is the foundation for world modeling, enabling tracking of entities, relationships, and properties over time.

Success criteria:

  • State captured in structured, queryable format
  • Entities and relationships clearly identified
  • Uncertainty and confidence explicitly represented
  • Evidence anchors for all state assertions

Compatible schemas:

  • schemas/output_schema.yaml
  • reference/world_state_schema.yaml

Inputs

ParameterRequiredTypeDescription
scopeYesstringWhat domain/system to model (e.g., "user authentication", "payment processing")
schemaNoobjectState schema defining expected structure
timestampNostringPoint in time for state (default: now)
depthNostringModeling depth: surface, detailed, comprehensive

Procedure

  1. Define scope boundaries: Clarify what is included in the state model

    • Identify system or domain boundaries
    • Determine entity types to include
    • Establish relationship types to capture
  2. Identify entities: Enumerate entities within scope

    • Extract entity references from sources
    • Assign unique identifiers
    • Capture entity properties/attributes
  3. Map relationships: Document connections between entities

    • Identify relationship types (contains, depends_on, references)
    • Note relationship directionality
    • Capture relationship properties
  4. Capture current values: Record current state of each entity

    • Document property values with evidence
    • Note uncertainty where values are unclear
    • Record observation timestamp
  5. Apply schema: Structure state according to schema if provided

    • Validate against schema constraints
    • Note schema violations or extensions needed
    • Ensure required fields are populated
  6. Ground state claims: Attach evidence to all assertions

    • Reference source files, commands, or observations
    • Note confidence level for each assertion

Output Contract

Return a structured object:

yaml
state:
  world_id: string  # Unique identifier for this state snapshot
  scope: string  # Domain being modeled
  timestamp: string  # When state was captured
  entities:
    - id: string  # Unique entity identifier
      type: string  # Entity classification
      properties: object  # Entity attributes
      confidence: number  # Confidence in entity state
  relationships:
    - from: string  # Source entity ID
      to: string  # Target entity ID
      type: string  # Relationship type
      properties: object  # Relationship attributes
  meta:
    version: string  # State schema version
    completeness: number  # 0-1 estimate of coverage
confidence: 0..1  # Overall state model confidence
evidence_anchors: ["file:line", "observation:id"]
assumptions: []

Field Definitions

FieldTypeDescription
state.world_idstringUnique identifier for state snapshot
state.scopestringDomain or system being modeled
state.entitiesarrayIdentified entities with properties
state.relationshipsarrayConnections between entities
state.meta.completenessnumberEstimated model completeness
confidencenumberOverall confidence in state accuracy

Examples

Example 1: Model Authentication System State

Input:

yaml
scope: "user authentication system"
depth: "detailed"

Output:

yaml
state:
  world_id: "auth-state-20240115-001"
  scope: "user authentication system"
  timestamp: "2024-01-15T10:30:00Z"
  entities:
    - id: "auth-service"
      type: "service"
      properties:
        status: "running"
        version: "2.3.1"
        port: 8080
      confidence: 0.95
    - id: "user-db"
      type: "database"
      properties:
        type: "PostgreSQL"
        connection_pool: 20
        active_connections: 12
      confidence: 0.90
    - id: "session-cache"
      type: "cache"
      properties:
        type: "Redis"
        memory_used: "256MB"
        keys: 15420
      confidence: 0.90
  relationships:
    - from: "auth-service"
      to: "user-db"
      type: "depends_on"
      properties:
        connection_type: "direct"
        required: true
    - from: "auth-service"
      to: "session-cache"
      type: "depends_on"
      properties:
        connection_type: "direct"
        required: true
  meta:
    version: "1.0"
    completeness: 0.85
confidence: 0.88
evidence_anchors:
  - "config/services.yml:15-45"
  - "command:docker ps"
  - "command:redis-cli info"
assumptions:
  - "Service discovery reflects actual running state"
  - "Configuration matches deployed state"

Example 2: Model Code Module State

Input:

yaml
scope: "payment processing module"
schema:
  required_entities: ["class", "method", "dependency"]

Output:

yaml
state:
  world_id: "payments-code-20240115"
  scope: "payment processing module"
  timestamp: "2024-01-15T11:00:00Z"
  entities:
    - id: "PaymentProcessor"
      type: "class"
      properties:
        file: "src/services/payment_processor.rb"
        lines: 145
        methods: 8
        complexity: 24
      confidence: 0.95
    - id: "process_payment"
      type: "method"
      properties:
        class: "PaymentProcessor"
        visibility: "public"
        params: ["order", "payment_method"]
        complexity: 12
      confidence: 0.95
    - id: "stripe-gem"
      type: "dependency"
      properties:
        name: "stripe"
        version: "8.0.0"
        usage: ["PaymentProcessor"]
      confidence: 0.90
  relationships:
    - from: "PaymentProcessor"
      to: "stripe-gem"
      type: "depends_on"
      properties:
        import_type: "require"
    - from: "process_payment"
      to: "PaymentProcessor"
      type: "member_of"
      properties:
        visibility: "public"
  meta:
    version: "1.0"
    completeness: 0.75
confidence: 0.85
evidence_anchors:
  - "src/services/payment_processor.rb:1-145"
  - "Gemfile:42"
assumptions:
  - "Static analysis reflects runtime behavior"
  - "No dynamic method definitions"

Verification

  • State includes world_id and timestamp
  • All entities have unique IDs and types
  • Relationships reference valid entity IDs
  • Confidence scores present for entities
  • Evidence anchors support state assertions

Verification tools: Read (to verify file references)

Safety Constraints

  • mutation: false
  • requires_checkpoint: false
  • requires_approval: false
  • risk: low

Capability-specific rules:

  • Do not modify state while modeling it
  • Note when state may be stale or dynamic
  • Flag entities with low confidence
  • Do not invent entities without evidence

Composition Patterns

Commonly follows:

  • observe - Observations feed into state modeling
  • retrieve - Retrieved data informs state
  • integrate - Merged data forms state

Commonly precedes:

  • transition - State enables transition modeling
  • compare - States can be compared (diff)
  • simulate - State is starting point for simulation

Anti-patterns:

  • Never use state for predictions (use predict)
  • Avoid state for single-value measurement (use measure)

Workflow references:

  • See reference/workflow_catalog.yaml#world_model_build for state in world modeling
  • See reference/workflow_catalog.yaml#digital_twin_sync_loop for state in digital twins