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- Steffen025/pai-opencode
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- 2026년 3월 28일 17:49
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/Steffen025/pai-opencode --skill agents명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| 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.