Agents - Custom Agent Composition System

Auto-routes when user mentions custom agents, agent creation, or specialized personalities.

Customization

Before executing, check for user customizations at: ~/.claude/skills/CORE/USER/SKILLCUSTOMIZATIONS/Agents/

If this directory exists, load and apply:

PREFERENCES.md - Named agent roster summary
VoiceConfig.json - Voice server configuration with ElevenLabs voice IDs
NamedAgents.md - Full agent backstories and character definitions (optional)

These define user-specific named agents with persistent identities. If the directory does not exist, use only dynamic agent composition from traits.

Overview

The Agents skill is a complete agent composition and management system. It consolidates all agent-related infrastructure:

Dynamic agent composition from traits (expertise + personality + approach)
Personality definitions and voice mappings
Custom agent creation with unique voices
Parallel agent orchestration patterns

Voice Notification

When executing a workflow, do BOTH:

Send voice notification:

curl -s -X POST http://localhost:8888/notify \
  -H "Content-Type: application/json" \
  -d '{"message": "Running the WORKFLOWNAME workflow from the Agents skill"}' \
  > /dev/null 2>&1 &

Output text notification:

Running the **WorkflowName** workflow from the **Agents** skill...

Full documentation: ~/.claude/skills/CORE/SkillNotifications.md

Workflow Routing

Available Workflows:

CREATECUSTOMAGENT - Create specialized custom agents → Workflows/CreateCustomAgent.md
LISTTRAITS - Show available agent traits → Workflows/ListTraits.md
SPAWNPARALLEL - Launch parallel agents → Workflows/SpawnParallelAgents.md

Examples

Example 1: Create custom agents for analysis

User: "Spin up 5 custom science agents to analyze this data"
→ Invokes CREATECUSTOMAGENT workflow
→ Runs AgentFactory 5 times with DIFFERENT trait combinations
→ Each agent gets unique personality + matched voice
→ Launches agents in parallel with model: "sonnet"

Example 2: List available traits

User: "What agent personalities can you create?"
→ Invokes LISTTRAITS workflow
→ Displays expertise (security, legal, finance, etc.)
→ Shows personality types (skeptical, enthusiastic, analytical, etc.)
→ Lists approach styles (thorough, rapid, systematic, etc.)

Example 3: Spawn parallel researchers

User: "Launch 10 agents to research these companies"
→ Invokes SPAWNPARALLEL workflow
→ Creates 10 Intern agents (generic, same voice)
→ Uses model: "haiku" for speed
→ Launches spotcheck agent after completion

Architecture

Hybrid Agent Model

The system uses two types of agents:

Type	Definition	Best For
Named Agents	Persistent identities with backstories (Remy, Ava, Marcus)	Recurring work, voice output, relationships
Dynamic Agents	Task-specific specialists composed from traits	One-off tasks, novel combinations, parallel work

The Agent Spectrum

┌─────────────────────────────────────────────────────────────────────┐
│   NAMED AGENTS          HYBRID USE          DYNAMIC AGENTS          │
│   (Relationship)        (Best of Both)      (Task-Specific)         │
├──────────────────────────────────────────────────────────────────────┤
│ Remy, Ava, Marcus   "Security expert      Ephemeral specialist      │
│                      with Johannes's      composed from traits      │
│                      skepticism"                                     │
└─────────────────────────────────────────────────────────────────────┘

Route Triggers

CRITICAL: The word "custom" is the KEY trigger:

User Says	What to Use	Why
"custom agents", "create custom agents"	AgentFactory	Unique prompts + unique voices
"agents", "launch agents", "bunch of agents"	Generic Interns	Same voice, parallel grunt work
"use Remy", "get Ava to"	Named agent	Pre-defined personality

Other triggers:

"agent personalities", "available traits" → LISTTRAITS workflow
"specialized agents", "expert in X" → CREATECUSTOMAGENT workflow
"parallel agents", "spawn 5 agents" → SPAWNPARALLEL workflow

Components

Data

Traits.yaml (Data/Traits.yaml)

Expertise areas: security, legal, finance, medical, technical, research, creative, business, data, communications
Personality dimensions: skeptical, enthusiastic, cautious, bold, analytical, creative, empathetic, contrarian, pragmatic, meticulous
Approach styles: thorough, rapid, systematic, exploratory, comparative, synthesizing, adversarial, consultative
Voice mappings: Trait combinations → ElevenLabs voices
Voice registry: 45+ voices with characteristics

Templates

DynamicAgent.hbs (Templates/DynamicAgent.hbs)

Handlebars template for dynamic agent prompts
Composes: expertise + personality + approach + voice assignment
Includes operational guidelines and response format

Tools

AgentFactory.ts (Tools/AgentFactory.ts)

Dynamic agent composition engine
Infers traits from task description
Maps trait combinations to appropriate voices
Outputs complete agent prompt ready for Task tool

# Usage examples
bun run ~/.claude/skills/Agents/Tools/AgentFactory.ts --task "Review security architecture"
bun run ~/.claude/skills/Agents/Tools/AgentFactory.ts --traits "legal,skeptical,meticulous"
bun run ~/.claude/skills/Agents/Tools/AgentFactory.ts --list

Personalities

AgentPersonalities.md (AgentPersonalities.md)

Named agent definitions with full backstories
Voice settings and personality traits
Character development and communication styles
JSON configuration for voice server

Named Agents:

Jamie - Expressive eager buddy
Rook Blackburn (Pentester) - Reformed grey hat
Priya Desai (Artist) - Aesthetic anarchist
Aditi Sharma (Designer) - Design school perfectionist
Dev Patel (Intern) - Brilliant overachiever
Ava Chen (Perplexity) - Investigative analyst
Ava Sterling (Claude) - Strategic sophisticate
Alex Rivera (Gemini) - Multi-perspective analyst
Marcus Webb (Engineer) - Battle-scarred leader
Serena Blackwood (Architect) - Academic visionary
Emma Hartley (Writer) - Technical storyteller

Integration Points

Voice Server (~/.claude/VoiceServer/)

Reads agent personality configuration from AgentPersonalities.md
Maps agent names to ElevenLabs voice IDs
Delivers personality-driven voice notifications

CORE Skill (~/.claude/skills/CORE/)

References Agents skill for custom agent creation
Documents the custom vs generic distinction
Includes agent creation in delegation patterns

Usage Patterns

For Users (Natural Language)

Users talk naturally:

"I need a legal expert to review this contract" → System composes legal + analytical + thorough agent
"Spin up 5 custom science agents" → System uses AgentFactory 5 times with different traits
"Launch agents to research these companies" → System spawns generic Intern agents
"Get me someone skeptical about security" → System composes security + skeptical + adversarial agent

Internal Process

When user says "custom agents", the assistant:

Invokes CREATECUSTOMAGENT workflow
Runs AgentFactory for EACH agent with DIFFERENT trait combinations
Gets unique prompt + voice ID for each
Launches agents using Task tool with the composed prompt
Each agent has a distinct personality-matched voice

Example internal execution:

# User: "Create 3 custom research agents"

# Agent 1
bun run AgentFactory.ts --traits "research,enthusiastic,exploratory"
# Output: Prompt with voice "Jeremy" (energetic)

# Agent 2
bun run AgentFactory.ts --traits "research,skeptical,thorough"
# Output: Prompt with voice "George" (intellectual)

# Agent 3
bun run AgentFactory.ts --traits "research,analytical,systematic"
# Output: Prompt with voice "Drew" (professional)

# Launch all 3 with Task tool
Task({ prompt: <agent1_prompt>, subagent_type: "Intern", model: "sonnet" })
Task({ prompt: <agent2_prompt>, subagent_type: "Intern", model: "sonnet" })
Task({ prompt: <agent3_prompt>, subagent_type: "Intern", model: "sonnet" })

Model Selection

Always specify the appropriate model:

Task Type	Model	Speed Multiplier
Grunt work, simple checks	`haiku`	10-20x faster
Standard analysis, research	`sonnet`	Balanced
Deep reasoning, architecture	`opus`	Maximum intelligence

Rule: Parallel agents especially benefit from haiku for speed.

Related Skills

CORE - Main system identity and delegation patterns
VoiceNarration - Voice output for content (separate from agent notifications)
Development - Uses Engineer and Architect agents

Version History

v1.0.0 (2025-12-16): Initial creation - consolidated all agent infrastructure into discrete skill