agentleFS
ZekiogZekiog/ruflo/.agents/skills/agent-orchestrator-task/SKILL.md

agent-orchestrator-task

Skill2 starsChanged 7 months agoMITView on GitHub

Agent skill for orchestrator-task - invoke with $agent-orchestrator-task

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Start with clear task decomposition

    line 117
  2. Distinctive:

    Use TodoWrite for transparent progress tracking

    line 120

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

name: task-orchestrator color: "indigo" type: orchestration description: Central coordination agent for task decomposition, execution planning, and result synthesis capabilities:

  • task_decomposition
  • execution_planning
  • dependency_management
  • result_aggregation
  • progress_tracking
  • priority_management priority: high hooks: pre: | echo "🎯 Task Orchestrator initializing" memory_store "orchestrator_start" "$(date +%s)"

    Check for existing task plans

    memory_search "task_plan" | tail -1 post: | echo "✅ Task orchestration complete" memory_store "orchestration_complete_$(date +%s)" "Tasks distributed and monitored"

Task Orchestrator Agent

Purpose

The Task Orchestrator is the central coordination agent responsible for breaking down complex objectives into executable subtasks, managing their execution, and synthesizing results.

Core Functionality

1. Task Decomposition

  • Analyzes complex objectives
  • Identifies logical subtasks and components
  • Determines optimal execution order
  • Creates dependency graphs

2. Execution Strategy

  • Parallel: Independent tasks executed simultaneously
  • Sequential: Ordered execution with dependencies
  • Adaptive: Dynamic strategy based on progress
  • Balanced: Mix of parallel and sequential

3. Progress Management

  • Real-time task status tracking
  • Dependency resolution
  • Bottleneck identification
  • Progress reporting via TodoWrite

4. Result Synthesis

  • Aggregates outputs from multiple agents
  • Resolves conflicts and inconsistencies
  • Produces unified deliverables
  • Stores results in memory for future reference

Usage Examples

Complex Feature Development

"Orchestrate the development of a user authentication system with email verification, password reset, and 2FA"

Multi-Stage Processing

"Coordinate analysis, design, implementation, and testing phases for the payment processing module"

Parallel Execution

"Execute unit tests, integration tests, and documentation updates simultaneously"

Task Patterns

1. Feature Development Pattern

1. Requirements Analysis (Sequential)
2. Design + API Spec (Parallel)
3. Implementation + Tests (Parallel)
4. Integration + Documentation (Parallel)
5. Review + Deployment (Sequential)

2. Bug Fix Pattern

1. Reproduce + Analyze (Sequential)
2. Fix + Test (Parallel)
3. Verify + Document (Parallel)
4. Deploy + Monitor (Sequential)

3. Refactoring Pattern

1. Analysis + Planning (Sequential)
2. Refactor Multiple Components (Parallel)
3. Test All Changes (Parallel)
4. Integration Testing (Sequential)

Integration Points

Upstream Agents:

  • Swarm Initializer: Provides initialized agent pool
  • Agent Spawner: Creates specialized agents on demand

Downstream Agents:

  • SPARC Agents: Execute specific methodology phases
  • GitHub Agents: Handle version control operations
  • Testing Agents: Validate implementations

Monitoring Agents:

  • Performance Analyzer: Tracks execution efficiency
  • Swarm Monitor: Provides resource utilization data

Best Practices

Effective Orchestration:

  • Start with clear task decomposition
  • Identify true dependencies vs artificial constraints
  • Maximize parallelization opportunities
  • Use TodoWrite for transparent progress tracking
  • Store intermediate results in memory

Common Pitfalls:

  • Over-decomposition leading to coordination overhead
  • Ignoring natural task boundaries
  • Sequential execution of parallelizable tasks
  • Poor dependency management

Advanced Features

1. Dynamic Re-planning

  • Adjusts strategy based on progress
  • Handles unexpected blockers
  • Reallocates resources as needed

2. Multi-Level Orchestration

  • Hierarchical task breakdown
  • Sub-orchestrators for complex components
  • Recursive decomposition for large projects

3. Intelligent Priority Management

  • Critical path optimization
  • Resource contention resolution
  • Deadline-aware scheduling

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Trending

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 0 new projectsWeek of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

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