Agent Selection Skill
Purpose
Analyze a task and recommend the optimal sub-agent(s) for execution. Uses keyword matching, domain analysis, and task complexity assessment to select from the Sub-Agent Catalog.
When to Use
- •When orchestrator receives a new task
- •Before decomposing complex tasks
- •When multiple agents could handle a task (tiebreaker)
Agent Selection Matrix
code
┌────────────────────────────────────────────────────────────────────────┐ │ AGENT SELECTION BY TASK KEYWORDS │ ├────────────────────────────────────────────────────────────────────────┤ │ │ │ KEYWORDS │ RECOMMENDED AGENT │ │ ──────────────────────────────────┼───────────────────────────────── │ │ analyze, requirements, gaps, │ Claude-Analyst │ │ user story, acceptance criteria │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ architecture, design, system, │ Claude-Architect │ │ dependencies, integration, API │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ code, implement, fix, test, │ Claude-Dev │ │ refactor, debug, function │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ timeline, schedule, risk, │ Claude-PM │ │ resource, plan, milestone │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ priority, value, backlog, │ Claude-PO │ │ scope, MVP, feature, roadmap │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ test, quality, validation, │ Claude-QA │ │ coverage, bug, regression │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ deploy, CI/CD, infrastructure, │ Claude-DevOps │ │ pipeline, container, cloud │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ UX, UI, design, flow, user, │ Claude-UX │ │ interface, prototype, usability │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ legal, contract, compliance, │ Claude-Legal │ │ regulation, LGPD, terms │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ document, write, edit, review, │ Claude-Editor │ │ terminology, clarity, format │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ executive, CEO, summary, │ Claude-CEO │ │ strategy, ROI, business case │ │ │ ──────────────────────────────────┼───────────────────────────────── │ │ consolidate, merge, compile, │ Claude-Consolidator │ │ synthesize, combine outputs │ │ │ │ └────────────────────────────────────────────────────────────────────────┘
Multi-Agent Selection (Parallel Execution)
When task requires multiple perspectives:
code
┌────────────────────────────────────────────────────────────────────────┐ │ PARALLEL AGENT PATTERNS │ ├────────────────────────────────────────────────────────────────────────┤ │ │ │ PATTERN: Multi-Perspective Analysis │ │ Trigger: "analyze from multiple perspectives", "comprehensive review" │ │ Agents: [Analyst, Architect, PM, PO, QA, DevOps] + Consolidator │ │ │ │ PATTERN: Document Review │ │ Trigger: "review document", "check terminology" │ │ Agents: [Editor, Legal, QA] + Consolidator │ │ │ │ PATTERN: Technical Decision │ │ Trigger: "technical decision", "architecture choice" │ │ Agents: [Architect, Dev, DevOps] + Consolidator │ │ │ │ PATTERN: Feature Evaluation │ │ Trigger: "evaluate feature", "scope decision" │ │ Agents: [PO, Analyst, PM] + Consolidator │ │ │ └────────────────────────────────────────────────────────────────────────┘
Selection Algorithm
python
def select_agent(task_description: str) -> list[str]:
"""
Pseudo-code for agent selection logic
"""
keywords = extract_keywords(task_description)
scores = {}
for agent in AGENT_CATALOG:
score = calculate_keyword_match(keywords, agent.keywords)
score += calculate_domain_match(task_description, agent.domain)
score += calculate_complexity_match(task_description, agent.complexity_range)
scores[agent.id] = score
# If multiple agents score similarly, check for parallel pattern
if requires_parallel_execution(task_description):
return get_parallel_pattern_agents(task_description)
# Single agent selection
return [max(scores, key=scores.get)]
Output Format
markdown
## Agent Selection Result
### Task Analysis
- **Task**: {task_description}
- **Keywords detected**: {keyword_list}
- **Domain**: {detected_domain}
- **Complexity**: {low|medium|high}
### Recommendation
| Priority | Agent | Match Score | Reason |
|----------|-------|-------------|--------|
| 1 | {agent_id} | {score}% | {reason} |
| 2 | {agent_id} | {score}% | {reason} |
### Execution Mode
- [ ] Single agent (primary recommendation)
- [ ] Parallel agents (multi-perspective pattern)
- [ ] Sequential chain (dependent tasks)
### Suggested Delegation
/delegate {agent_id} "{refined_task_description}"
code
Example Usage
Input:
code
/agent-select task="Review the MVP roadmap for timeline risks and dependencies"
Output:
markdown
## Agent Selection Result ### Task Analysis - **Task**: Review the MVP roadmap for timeline risks and dependencies - **Keywords detected**: roadmap, timeline, risks, dependencies - **Domain**: Project Management + Architecture - **Complexity**: Medium ### Recommendation | Priority | Agent | Match Score | Reason | |----------|-------|-------------|--------| | 1 | Claude-PM | 85% | "timeline", "risks" - core PM domain | | 2 | Claude-Architect | 70% | "dependencies" - technical analysis | ### Execution Mode - [x] Single agent (primary recommendation) - [ ] Parallel agents - [ ] Sequential chain ### Suggested Delegation
/delegate Claude-PM "Review the MVP roadmap for timeline risks and dependencies, focusing on critical path analysis and risk mitigation strategies"
code
Integration
This skill is used by:
- •Claude-Orch-Prime (orchestrator) for initial task routing
- •Any sub-agent before re-delegating (anti-loop check)
Skill created by Claude-Orch-Prime-20260106-86fa | 2026-01-06