Multi-Agent Today's Tasks Workflow

Last Updated: 2025-03-01 Component: Today's Workflow Service

📅 Overview

The Today's Tasks Workflow is an automated, intelligent system that generates a personalized daily to-do list for the user. Unlike static templates or generic AI prompts, this system uses a Multi-Agent Committee to analyze real-time data and propose high-value actions.

🏗️ Architecture: The "Committee" Model

The workflow follows a Manager-Worker pattern where the TodayWorkflowGenerator acts as the Orchestrator.

sequenceDiagram
    participant User
    participant Orchestrator
    participant Agents (Committee)
    participant Memory (SIF)
    
    User->>Orchestrator: Loads Dashboard
    Orchestrator->>Orchestrator: Checks for existing plan
    alt No Plan for Today
        Orchestrator->>Agents: "Propose tasks for [User Context]"
        par Parallel Execution
            Agents->>Agents: Analyze GSC, Trends, Gaps
        end
        Agents-->>Orchestrator: [Task Proposals]
        Orchestrator->>Memory: Filter Redundant/Rejected?
        Memory-->>Orchestrator: Filtered List
        Orchestrator->>Orchestrator: Consolidate & Prioritize
        Orchestrator->>User: Daily Plan
    else Plan Exists
        Orchestrator->>User: Existing Plan
    end

🧠 The Intelligence Layer

1. Proposal Phase (The "Workers")

Each agent submits proposals based on its domain:

Agent	Data Source	Sample Proposal
Strategy Architect	Content Pillars	"Review 'AI Trends' pillar - performance dropped 10%."
Content Strategist	Competitor Content	"Draft post on 'Vector Search' (Competitor Gap)."
SEO Specialist	Search Console	"Fix 404 error on /pricing page."
Social Manager	Engagement Metrics	"Reply to 3 comments on LinkedIn post."
Competitor Analyst	Market Signals	"Competitor X launched feature Y. Monitor impact."

2. Orchestration Phase (The "Manager")

The TodayWorkflowGenerator:

Gathers: Collects all proposals via asyncio.gather.
Deduplicates: Merges similar tasks (e.g., if SEO and Content agents both suggest the same blog update).
Formats: Converts raw proposals into the frontend-ready TodayTask schema.

3. Self-Learning Phase (The "Brain")

The system uses TaskMemoryService and txtai to improve over time.

Rejected Tasks: If a user dismisses a task, it is indexed as "negative feedback." The system semantically checks future proposals against this index to avoid nagging.
Completed Tasks: Completed tasks are recorded to prevent suggesting the same non-recurring task too soon.

🛠️ Data Models

TaskProposal (Internal)

@dataclass
class TaskProposal:
    title: str
    description: str
    pillar_id: str          # plan, generate, publish, analyze, engage, remarket
    priority: str           # high, medium, low
    estimated_time: int     # minutes
    source_agent: str       # e.g., "SEOOptimizationAgent"
    reasoning: str          # "Detected 404 error spike"
    context_data: Dict      # Payload for the action button

TaskHistory (Database)

Tracks the lifecycle for learning:

task_hash: SHA-256 of title+desc for fast deduplication.
status: completed / dismissed.
feedback: User provided notes.
vector_id: Link to the semantic index entry.

🎨 UI Experience

The Card: Each task appears as a card in the "Today's Workflow" modal.
Transparency:
- Badge: "Suggested by [Agent Name]"
- Tooltip: "Why? [Reasoning]" (e.g., "Because traffic dropped 15%").
Feedback:
- Complete: Triggers positive reinforcement learning.
- Dismiss: Triggers negative reinforcement learning.

🔄 Lifecycle & Triggers

Daily Reset: The plan is generated once per day (UTC).
Persistence: Tasks remain "in progress" until marked done or the day ends.
On-Demand: Users can manually trigger a regeneration if the day's plan is empty or irrelevant.

4.0 KiB Raw Blame History