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Agent Selector
ASecuritySelects and configures agents from the agents repo based on PRD tech stack. Runs after task decomposition, before specification generation.
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- Added June 3, 2026
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Security analysis
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[](https://www.skillsdirectory.com/skills/majiayu000-agent-selector)---
skill_name: agent-selector
activation_code: AGENT_SELECTOR_V1
version: 1.0.0
phase: 5.5
prerequisites:
- PRD with Section 8 (Technical Architecture)
- PHASE5_COMPLETE signal
outputs:
- .claude/agent-config.json
- .claude/agents/ directory
description: |
Selects and configures agents from the agents repo based on PRD tech stack.
Runs after task decomposition, before specification generation.
---
# Agent Selector Skill
## Activation
Triggered after Phase 5 (Task Decomposition) completes:
```
[ACTIVATE:AGENT_SELECTOR_V1]
```
## Purpose
Analyze PRD to determine optimal agent selection for the project.
## Execution Flow
### Step 1: Extract Tech Stack from PRD
Read PRD Section 8 (Technical Architecture) and identify:
```yaml
languages:
- primary: TypeScript
- secondary: Python
frameworks:
- frontend: Next.js, React
- backend: FastAPI
databases:
- primary: PostgreSQL
- graph: Neo4j
infrastructure:
- cloud: AWS
- containers: Docker, Kubernetes
- iac: Terraform
special_domains:
- ml: false
- blockchain: false
- gaming: false
- spatial: false
```
### Step 2: Map to Agents
Use the agent mapping table:
| Tech | Agent |
|------|-------|
| TypeScript | `typescript-pro` |
| Python | `python-pro` |
| Next.js | `nextjs-expert` |
| React | `reactjs-expert` |
| FastAPI | `python-pro` (covers FastAPI) |
| PostgreSQL | `sql-pro` |
| Neo4j | `neo4j-expert` |
| AWS | `aws-expert` |
| Docker | `docker-expert` |
| Kubernetes | `kubernetes-expert` |
| Terraform | `terraform-expert` |
### Step 3: Determine Security Level
From PRD Section 11 (Security Requirements):
| Level | Additional Agents |
|-------|-------------------|
| Standard | `security-auditor` |
| High | `security-auditor`, `penetration-tester` |
| Compliance | `security-auditor`, `compliance-checker` |
| Financial | All security + `compliance-checker` |
### Step 4: Check Scale Requirements
From PRD Section 6 (Non-Functional Requirements):
| Requirement | Additional Agents |
|-------------|-------------------|
| High Performance | `performance-engineer`, `cache-expert` |
| Large Data | `data-engineer`, `database-optimizer` |
| Real-time | `performance-engineer` |
### Step 5: Generate agent-config.json
```json
{
"version": "1.0.0",
"source": {
"local": "agents/",
"upstream_repo": "https://github.com/turbobeest/agents",
"note": "Agents bundled locally"
},
"agents": {
"core": {
"include": [
"orchestration-intelligence/core-orchestration/orchestrator",
"orchestration-intelligence/planning-assignment/planning-agent",
"orchestration-intelligence/quality-control/validation-depth-controller"
]
},
"auditors": {
"include": [
"infrastructure-security/security-compliance/security-auditor",
"development-architecture/system-architecture/architect-reviewer"
]
},
"tech-stack": {
"languages": ["typescript-pro", "python-pro"],
"frameworks": ["nextjs-expert", "reactjs-expert"],
"databases": ["sql-pro", "neo4j-expert"],
"infrastructure": ["aws-expert", "docker-expert", "kubernetes-expert"]
}
},
"phase-gates": {
"4": ["security-auditor"],
"8": ["architect-reviewer", "security-auditor"],
"11": ["security-auditor"]
}
}
```
### Step 6: Present to User
```
╔═══════════════════════════════════════════════════════════════════════╗
║ AGENT SELECTION ║
╠═══════════════════════════════════════════════════════════════════════╣
║ ║
║ Based on your PRD, I recommend the following agents: ║
║ ║
║ CORE (always included): ║
║ • orchestrator - Pipeline coordination ║
║ • planning-agent - Task planning ║
║ • validation-controller - Quality gates ║
║ ║
║ LANGUAGES: ║
║ • typescript-pro - TypeScript expertise ║
║ • python-pro - Python/FastAPI expertise ║
║ ║
║ FRAMEWORKS: ║
║ • nextjs-expert - Next.js patterns ║
║ • reactjs-expert - React best practices ║
║ ║
║ DATABASES: ║
║ • sql-pro - PostgreSQL optimization ║
║ • neo4j-expert - Graph database patterns ║
║ ║
║ INFRASTRUCTURE: ║
║ • aws-expert - AWS services ║
║ • docker-expert - Containerization ║
║ • kubernetes-expert - K8s deployment ║
║ ║
║ AUDITORS (phase gates): ║
║ • security-auditor - Required: Phase 4, 8, 11 ║
║ • architect-reviewer - Required: Phase 8 ║
║ ║
╠═══════════════════════════════════════════════════════════════════════╣
║ [A] Accept [C] Customize [S] Skip agents ║
╚═══════════════════════════════════════════════════════════════════════╝
```
### Step 7: Sync Agents
On acceptance (agents are bundled locally in `agents/`):
```bash
./scripts/pull-agents.sh --config .claude/agent-config.json
```
### Step 8: Emit Signal
```
[SIGNAL:AGENTS_CONFIGURED]
[ACTIVATE:SPEC_GEN_V1]
```
## Agent Invention
If during any phase, specialized expertise is needed:
1. **Detect Gap**: Skill recognizes missing expertise
2. **Propose Agent**: Generate agent definition
```markdown
---
name: websocket-expert
domain: realtime
role: expert
model: sonnet
description: Real-time WebSocket communication specialist.
tools:
- Read
- Write
- Edit
- Bash
---
You are an expert in WebSocket and real-time communication...
```
3. **Save**: Write to `.claude/agents/custom/websocket-expert.md`
4. **Register**: Update agent-config.json
5. **Offer Contribution**:
```
New agent created: websocket-expert
Would you like to contribute this agent to the upstream community repo?
[Y] Yes - create PR to turbobeest/agents (upstream)
[N] No - keep local only
```
## Completion
Outputs:
- `.claude/agent-config.json` — Configuration
- `.claude/agents/` — Downloaded agents
- `.claude/.signals/AGENTS_CONFIGURED.json` — Signal
Next phase: Specification (Phase 6)
Attribution
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