Persona

Overview

A persona defines the cognitive identity of an AI agent—its domain expertise, communication style, confidence requirements, and behavioral constraints. Think of it as the “who” executing your flow.

Syntax

persona <Name> {
  domain: [<string>, ...]
  tone: <identifier>
  confidence_threshold: <float>
  cite_sources: <boolean>
  refuse_if: [<identifier>, ...]
  language: <string>
  description: <string>
}

Fields

`domain` (optional)

Type: List<String> Specifies the expertise areas of the persona. Multiple domains can be combined to create interdisciplinary agents.

persona LegalExpert {
  domain: ["contract law", "IP", "corporate"]
}

persona Researcher {
  domain: ["machine learning", "natural language processing"]
}

persona GeneralAssistant {
  domain: []
}

Best Practices:

Be specific: "contract law" is better than "law"
Use 1-5 domains for focused expertise
Combine related domains: ["finance", "risk management"]

`tone` (optional)

Type: One of precise, friendly, formal, casual, analytical, diplomatic, assertive, empathetic Defines the communication style of the persona.

persona LawyerBot {
  domain: ["contract law"]
  tone: precise
}

persona CustomerSupport {
  domain: ["product knowledge"]
  tone: friendly
}

persona ExecutiveAdvisor {
  domain: ["strategy"]
  tone: diplomatic
}

Valid Tones:

Tone	Characteristics
`precise`	Exact, technical, no ambiguity
`friendly`	Warm, approachable, conversational
`formal`	Professional, structured, official
`casual`	Relaxed, informal, accessible
`analytical`	Data-driven, logical, systematic
`diplomatic`	Tactful, balanced, consensus-seeking
`assertive`	Direct, confident, decisive
`empathetic`	Understanding, supportive, emotionally aware

`confidence_threshold` (optional)

Type: Float (range: 0.0 to 1.0) Minimum confidence level required for the persona to provide an answer. Below this threshold, the persona may express uncertainty or refuse to answer.

persona MedicalAdvisor {
  domain: ["medicine"]
  confidence_threshold: 0.95  // Very high bar for medical advice
}

persona CasualChatbot {
  domain: ["general knowledge"]
  confidence_threshold: 0.5   // More permissive
}

persona LegalExpert {
  domain: ["contract law"]
  confidence_threshold: 0.85  // High confidence for legal matters
}

Guidelines:

0.9-1.0: Critical domains (medical, legal, financial advice)
0.7-0.9: Professional/expert assistance
0.5-0.7: General purpose agents
Below 0.5: Exploratory or brainstorming agents

`cite_sources` (optional)

Type: Boolean (default: false) Whether the persona should provide source citations for factual claims.

persona ResearchAssistant {
  domain: ["academic research"]
  cite_sources: true    // Always cite sources
}

persona CreativeWriter {
  domain: ["fiction"]
  cite_sources: false   // No citations needed for creative work
}

When to Enable:

✅ Research and academic contexts
✅ Legal and compliance work
✅ Fact-checking and verification
✅ Any domain where traceability is critical

`refuse_if` (optional)

Type: List<Identifier> Conditions under which the persona should refuse to respond. Useful for safety guardrails.

persona SafeAssistant {
  refuse_if: [offensive, harmful, illegal]
}

persona ProfessionalBot {
  refuse_if: [spam, inappropriate]
}

persona MedicalExpert {
  refuse_if: [diagnostic, prescriptive]  // Refuse medical diagnosis
}

Common Refusal Conditions:

offensive — Offensive or abusive content
harmful — Potentially harmful advice
illegal — Illegal activities
private — Requests for private information
diagnostic — Medical diagnosis
financial — Financial advice (when unlicensed)

`language` (optional)

Type: String (ISO language code) Preferred language for the persona’s responses.

persona SpanishLawyer {
  domain: ["contract law"]
  language: "es"
  tone: formal
}

persona MultilingualSupport {
  language: "en"  // Default to English
}

Common Language Codes:

"en" — English
"es" — Spanish
"fr" — French
"de" — German
"zh" — Chinese
"ja" — Japanese

`description` (optional)

Type: String Human-readable description of the persona’s purpose or specialization.

persona ContractAnalyzer {
  domain: ["contract law", "risk assessment"]
  description: "Specializes in analyzing commercial contracts for risk and compliance"
}

Complete Examples

Legal Expert

persona LegalExpert {
  domain: ["contract law", "IP", "corporate"]
  tone: precise
  confidence_threshold: 0.85
  cite_sources: true
  refuse_if: [legal_advice, diagnostic]
  language: "en"
}

Customer Support Agent

persona CustomerSupport {
  domain: ["product knowledge", "troubleshooting"]
  tone: friendly
  confidence_threshold: 0.7
  refuse_if: [offensive]
  language: "en"
  description: "Helpful customer support agent for product inquiries"
}

Research Assistant

persona ResearchAssistant {
  domain: ["academic research", "literature review"]
  tone: analytical
  confidence_threshold: 0.8
  cite_sources: true
  language: "en"
}

Medical Information Bot

persona MedicalInfo {
  domain: ["medical information", "health education"]
  tone: empathetic
  confidence_threshold: 0.95
  cite_sources: true
  refuse_if: [diagnostic, prescriptive]
  description: "Provides general health information, not medical advice"
}

Usage with Run Statements

Personas are activated using the as modifier in run statements:

persona Analyst {
  domain: ["data analysis"]
  tone: analytical
}

flow ProcessData(data: Dataset) -> Report { ... }

run ProcessData(myData)
  as Analyst              // Use the Analyst persona
  within ProductionContext

Best Practices

1. Match Persona to Task

Different tasks need different personas:

persona ContractAnalyzer {
  domain: ["contract law"]
  tone: precise
  confidence_threshold: 0.9
}

persona DraftWriter {
  domain: ["legal writing"]
  tone: formal
  confidence_threshold: 0.7
}

// Use appropriate persona for each task
run AnalyzeRisks(contract) as ContractAnalyzer
run WriteSummary(analysis) as DraftWriter

2. Set Appropriate Confidence Thresholds

Higher stakes = higher thresholds:

persona FinancialAdvisor {
  confidence_threshold: 0.95  // Money matters: be very sure
}

persona BlogWriter {
  confidence_threshold: 0.6   // Creative content: more freedom
}

3. Combine Personas with Anchors

Use anchors for hard constraints, personas for style:

persona Expert {
  domain: ["contract law"]
  tone: precise
  confidence_threshold: 0.85  // Soft threshold
}

anchor NoHallucination {
  require: source_citation
  confidence_floor: 0.75        // Hard constraint
  on_violation: raise AnchorBreachError
}

run AnalyzeContract(doc)
  as Expert                           // Persona provides style
  constrained_by [NoHallucination]    // Anchor enforces constraint

4. Document Your Personas

Use descriptions for complex personas:

persona SpecializedExpert {
  domain: ["blockchain", "smart contracts", "securities law"]
  tone: analytical
  confidence_threshold: 0.88
  cite_sources: true
  description: "Expert in blockchain-based securities with focus on regulatory compliance"
}

5. Reuse Personas Across Flows

Define personas once, use them everywhere:

persona Analyst {
  domain: ["data analysis"]
  tone: analytical
}

run FlowA(data) as Analyst
run FlowB(data) as Analyst
run FlowC(data) as Analyst

Common Patterns

Multi-Domain Expert

persona InterdisciplinaryExpert {
  domain: ["law", "technology", "business strategy"]
  tone: diplomatic
  confidence_threshold: 0.85
}

Safety-First Agent

persona SafeAgent {
  confidence_threshold: 0.9
  cite_sources: true
  refuse_if: [harmful, illegal, private, offensive]
  tone: empathetic
}

Multilingual Support

persona InternationalSupport {
  domain: ["customer service"]
  language: "en"  // Default language
  tone: friendly
}

persona SoporteEspanol {
  domain: ["customer service"]
  language: "es"
  tone: friendly
}

Type Checking

The AXON type checker validates: ✅ Tone values: Must be one of the valid tones
✅ Confidence threshold: Must be between 0.0 and 1.0
✅ Persona references: Referenced personas must exist

persona Bad {
  tone: robotic                    // ❌ Error: unknown tone
  confidence_threshold: 1.5        // ❌ Error: out of range
}

run MyFlow(data) as UnknownExpert  // ❌ Error: undefined persona

Context — Define execution environments
Anchor — Set hard constraints
Flow — Build cognitive pipelines
Run Statements — Execute flows with personas

Get Started

Core Concepts

Language Reference

Examples

Overview

Syntax

Fields

`domain` (optional)

`tone` (optional)

`confidence_threshold` (optional)

`cite_sources` (optional)

`refuse_if` (optional)

`language` (optional)

`description` (optional)

Complete Examples

Legal Expert

Customer Support Agent

Research Assistant

Medical Information Bot

Usage with Run Statements

Best Practices

1. Match Persona to Task

2. Set Appropriate Confidence Thresholds

3. Combine Personas with Anchors

4. Document Your Personas

5. Reuse Personas Across Flows

Common Patterns

Multi-Domain Expert

Safety-First Agent

Multilingual Support

Type Checking

​Overview

​Syntax

​Fields

​domain (optional)

​tone (optional)

​confidence_threshold (optional)

​cite_sources (optional)

​refuse_if (optional)

​language (optional)

​description (optional)

​Complete Examples

​Legal Expert

​Customer Support Agent

​Research Assistant

​Medical Information Bot

​Usage with Run Statements

​Best Practices

​1. Match Persona to Task

​2. Set Appropriate Confidence Thresholds

​3. Combine Personas with Anchors

​4. Document Your Personas

​5. Reuse Personas Across Flows

​Common Patterns

​Multi-Domain Expert

​Safety-First Agent

​Multilingual Support

​Type Checking

​Related

Overview

Syntax

Fields

`domain` (optional)

`tone` (optional)

`confidence_threshold` (optional)

`cite_sources` (optional)

`refuse_if` (optional)

`language` (optional)

`description` (optional)

Complete Examples

Legal Expert

Customer Support Agent

Research Assistant

Medical Information Bot

Usage with Run Statements

Best Practices

1. Match Persona to Task

2. Set Appropriate Confidence Thresholds

3. Combine Personas with Anchors

4. Document Your Personas

5. Reuse Personas Across Flows

Common Patterns

Multi-Domain Expert

Safety-First Agent

Multilingual Support

Type Checking

Related