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multi-agent-architecture

Agent Building
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Multi-agent sistem mimarisi referansi. Use when working with agents, pipelines, or understanding the content generation workflow.

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  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/data/multi-agent-architecture/SKILL.md

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Multi-Agent Architecture

Agent Overview

AgentRoleKey Action
OrchestratorKoordinasyonplan_week, daily_check
PlannerKonu secimisuggest_topic
CreatorIcerik uretimicreate_post, create_visual_prompt
ReviewerKalite kontrolreview_post (score 1-10)
PublisherPlatform yayinpublish
AnalyticsPerformans takipfetch_metrics

Pipeline Types

TypeTelegram Approval
dailyYes (each stage)
autonomousNo (min_score check)
reelsYes
carouselYes

Daily Pipeline Flow

Planner → suggest_topic
    ↓ Telegram approval
Creator → create_post
    ↓ Telegram approval
Creator → create_visual_prompt → Flux/Veo
    ↓ Telegram approval
Reviewer → review_post (score)
    ↓ Telegram approval
Publisher → Instagram

Pipeline States

IDLE → PLANNING → AWAITING_TOPIC_APPROVAL →
CREATING_CONTENT → AWAITING_CONTENT_APPROVAL →
CREATING_VISUAL → AWAITING_VISUAL_APPROVAL →
REVIEWING → AWAITING_FINAL_APPROVAL →
PUBLISHING → COMPLETED | ERROR

Basic Usage

from app.scheduler.pipeline import ContentPipeline

pipeline = ContentPipeline(telegram_callback=callback)

# Daily (with approvals)
result = await pipeline.run_daily_content()

# Autonomous (no approvals, min_score=7)
result = await pipeline.run_autonomous_content(min_score=7)

# Reels
result = await pipeline.run_reels_content()

BaseAgent Pattern

from app.agents.base_agent import BaseAgent

class MyAgent(BaseAgent):
    def __init__(self):
        super().__init__("myagent")  # Loads persona

    async def execute(self, input_data):
        response = await self.call_claude_with_retry(
            prompt="...",
            timeout=120,
            max_retries=3
        )
        return json.loads(response)

Retry Logic

@retry_with_backoff(max_retries=3, base_delay=2.0)
# Delays: 2s, 4s, 8s (exponential)

Return Format

# Success
{"success": True, "post_id": 123, "instagram_post_id": "..."}

# Error
{"success": False, "error": "...", "final_state": "error"}

Deep Links

  • app/scheduler/pipeline.py - Pipeline logic
  • app/agents/base_agent.py - Base class
  • app/agents/creator.py - Content creation
  • app/agents/reviewer.py - Quality control
  • context/agent-personas/ - Agent personas