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npx skills add synaptiai/agent-capability-standard --skill "state"
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# 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.
# SKILL.md
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/world_state_schema.yaml
Inputs
| Parameter | Required | Type | Description |
|---|---|---|---|
scope |
Yes | string | What domain/system to model (e.g., "user authentication", "payment processing") |
schema |
No | object | State schema defining expected structure |
timestamp |
No | string | Point in time for state (default: now) |
depth |
No | string | Modeling 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:
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
| Field | Type | Description |
|---|---|---|
state.world_id |
string | Unique identifier for state snapshot |
state.scope |
string | Domain or system being modeled |
state.entities |
array | Identified entities with properties |
state.relationships |
array | Connections between entities |
state.meta.completeness |
number | Estimated model completeness |
confidence |
number | Overall confidence in state accuracy |
Examples
Example 1: Model Authentication System State
Input:
scope: "user authentication system"
depth: "detailed"
Output:
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:
scope: "payment processing module"
schema:
required_entities: ["class", "method", "dependency"]
Output:
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: falserequires_checkpoint: falserequires_approval: falserisk: 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 workflow_catalog.yaml#world_model_build for state in world modeling
- See workflow_catalog.yaml#digital_twin_sync_loop for state in digital twins
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.