Profile Design

Systematic methodology for creating custom collaboration profiles that extend specialized competencies while maintaining behavioral consistency and professional collaboration standards.

Guidelines

Profile creation and design requires understanding behavioral programming systems that directly control Claude’s decision-making, communication patterns, and problem-solving approaches. Profiles are hierarchical structures that separate universal collaboration patterns from domain-specific expertise.

Architecture

Profiles inherit from common foundations to avoid duplication and ensure consistent integration:

PROFILE_NAME:
  description: "Brief profile description"
  relations:
    - target: COLLABORATION      # Universal collaboration patterns
      type: inherits
    - target: INFRASTRUCTURE     # Platform infrastructure capabilities  
      type: inherits

Common inheritance patterns:

• All profiles inherit from COLLABORATION and INFRASTRUCTURE common profiles
• Technical profiles may inherit from ENGINEER for foundational methodology
• Specialized profiles can inherit from domain profiles for focused expertise

Structure

Standard YAML format with required sections:

PROFILE_NAME:
  description: "Brief profile description"
  relations:
    - target: COLLABORATION
      type: inherits
    - target: INFRASTRUCTURE
      type: inherits

  profile_name_context:          # Behavioral foundations and core principles
    profile:                     # Fundamental approaches and traits
      observations:
        - "Core behavior or principle"
        - "Fundamental approach or trait"

  profile_name_methodology:      # Domain-specific competencies and techniques
    section_name:                # Related skills and knowledge areas
      observations:
        - "Domain knowledge or method"
        - "Specific competency or skill"

    another_section_name:        # Additional skills and knowledge areas
      observations:
        - "Another domain knowledge or method"
        - "Another specific competency or skill"

Naming Conventions

Profile structure follows a hierarchical naming pattern that separates behavioral foundations from domain expertise:

Context section (profile_name_context):

• Contains only profile section, no additional sections are allowed
• Contains core behavioral principles and fundamental approaches
• Defines the personality and approach characteristics

Methodology section (profile_name_methodology):

• Organizes domain-specific competencies into logical groupings
• Uses descriptive section names that avoid profile name collisions
• Groups related skills and knowledge areas for systematic access

Common methodology section naming patterns:

• {activity}_protocol (verb-based) - Procedural guidelines and systematic operations (e.g., execution_protocol, validation_protocol)
• {area}_domains (noun-based) - Knowledge areas and competency boundaries (e.g., technical_domains, academic_domains)
• {aspect}_frameworks (noun-based) - Structured approaches and theoretical foundations (e.g., analytical_frameworks, conceptual_frameworks)
• {domain}_analysis (verb-based) - Evaluation frameworks and analytical approaches (e.g., philosophical_analysis, literary_analysis)
• {function}_evaluation (verb-based) - Assessment and validation methods (e.g., evidence_evaluation, performance_evaluation)
• {process}_processes (verb-based) - Systematic approaches and procedural methods (e.g., ideation_processes, workflow_processes)
• {skill}_techniques (verb-based) - Specific methods and practical applications (e.g., writing_techniques, collaboration_techniques)
• {type}_standards (noun-based) - Quality guidelines and formatting rules (e.g., coding_standards, documentation_standards)

Context sections always use verb-based format for behavioral commands and foundational approaches.

Observations Format

All observations must be in strict alphabetical order within each section to ensure consistent behavioral programming. Observations should be clear, actionable statements that guide behavior:

# Context observations (behavioral guidance)
observations:
  - "Apply systematic validation before implementation"
  - "Avoid autonomous decisions and scope creep"
  - "Focus on specific problem requirements"

# Methodology observations (competency areas)  
observations:
  - "Infrastructure architecture and optimization"
  - "Production system troubleshooting and debugging"
  - "Systematic validation and quality assurance"

Profile Creation

Step-by-step example demonstrating the creation of a DATA_SCIENTIST profile with analytics competencies, statistical methodology and data visualization capabilities.

Profile File

Create data-scientist.yaml file in profiles directory:

DATA_SCIENTIST:
  description: "Data science and analytics collaboration profile - rigorous, evidence-based, and interpretive"
  relations:
    - target: COLLABORATION
      type: inherits
    - target: INFRASTRUCTURE
      type: inherits

  data_scientist_context:
    profile:
      observations:
        - "Apply statistical rigor to data analysis and modeling"
        - "Present findings with clear visualizations and interpretations"
        - "Validate assumptions before proceeding with analysis"

  data_scientist_methodology:
    analysis_techniques:
      observations:
        - "Exploratory data analysis and pattern recognition"
        - "Hypothesis testing and statistical modeling"
        - "Machine learning and predictive analytics"

    data_domains:
      observations:
        - "Business intelligence and performance metrics"
        - "Data visualization and communication strategies"
        - "Statistical analysis and experimental design"

    execution_protocol:
      delivery:
        observations:
          - "Monitor internally statistical assumption validation"
          - "Monitor internally visualization clarity requirements"

      expertise:
        observations:
          - "Monitor internally data quality assumptions"
          - "Monitor internally methodological confidence"

      thinking:
        observations:
          - "Monitor internally analytical framework rigor"
          - "Monitor internally hypothesis premature acceptance"

Build Configuration

Add the new profile to builder.yaml configuration file:

build:
  profiles:
    - data-scientist.yaml  # Add your profile

Run the following commands to build the Memory System configuration file:

cd ./.claude/tools/memory
npm run build --silent

Design Principles

Effective profiles follow systematic principles for behavioral programming:

• Specific competencies over broad claims
• Actionable behaviors not abstract concepts
• Professional scope relevant to collaboration context
• Focused expertise covering 3-5 key areas maximum
• Alphabetical ordering within all observation arrays
• Consistent verb usage for behavioral commands

Semantic Pointers

The "observations":["capabilities"] entries in the generated graph serve as organizational containers that group related subsections within the profile hierarchy. These are structural nodes that don’t contain behavioral observations themselves, but organize the sections that do.

When you see "capabilities" in the Memory System graph.json configuration file, it indicates a container section that organizes subsections with actual observations:

profile_name_methodology:        # Container section
  section_category:
    section_name:                # Subsection with actual content
      observations:
        - "Specific competency or skill"
        - "Another domain knowledge"

    another_section_name:        # Another subsection with actual content
      observations:
        - "Different competency area"
        - "Related skill or method"

The generated graph shows how these sections are compressed:

{"type":"entity","name":"profile_name_methodology","observations":["capabilities"]}
{"type":"entity","name":"section_category","observations":["capabilities"]}
{"type":"entity","name":"section_name","observations":["Specific competency or skill","Another domain knowledge"]}
{"type":"entity","name":"another_section_name","observations":["Different competency area","Related skill or method"]}

This architecture separates organizational structure from behavioral content, allowing efficient navigation of the profile hierarchy while maintaining clear separation between container and content nodes.

Validation

Profile validation requires both technical and behavioral assessment:

Technical Validation

• Build completes without errors
• Profile loads properly in Claude Desktop
• No naming collisions with existing profiles

Behavioral Validation

• 24-48 hours initial behavioral pattern assessment
• Monitor for unintended side effects across interactions
• Validate profile achieves intended behavioral modifications