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Dynamic agent composition. USE WHEN custom agents, agent personalities, traits, voices.
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Basado en la clasificación ocupacional SOC
| name | Agents |
| description | Dynamic agent composition. USE WHEN custom agents, agent personalities, traits, voices. |
Auto-routes when user mentions custom agents, agent creation, or specialized personalities.
Before executing, check for user customizations at:
~/.opencode/PAI/USER/SKILLCUSTOMIZATIONS/Agents/
If this directory exists, load and apply:
PREFERENCES.md - Named agent roster summaryVoiceConfig.json - Voice server configuration with ElevenLabs voice IDsNamedAgents.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.
The Agents skill is a complete agent composition and management system. It consolidates all agent-related infrastructure:
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...
Available Workflows:
Workflows/CreateCustomAgent.mdWorkflows/ListTraits.mdWorkflows/SpawnParallelAgents.mdExample 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
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 |
┌─────────────────────────────────────────────────────────────────────┐
│ 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" │
└─────────────────────────────────────────────────────────────────────┘
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:
Traits.yaml (Data/Traits.yaml)
DynamicAgent.hbs (Templates/DynamicAgent.hbs)
AgentFactory.ts (Tools/AgentFactory.ts)
# Usage examples
bun run ~/.opencode/skills/Agents/Tools/AgentFactory.ts --task "Review security architecture"
bun run ~/.opencode/skills/Agents/Tools/AgentFactory.ts --traits "legal,skeptical,meticulous"
bun run ~/.opencode/skills/Agents/Tools/AgentFactory.ts --list
AgentPersonalities.md (AgentPersonalities.md)
Named Agents:
Voice Server (~/.opencode/VoiceServer/)
PAI Skill (~/.opencode/PAI/)
Users talk naturally:
When user says "custom agents", the assistant:
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" })
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.
Personal AI Infrastructure core. The authoritative reference for how PAI works.
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