Task Orchestra

Coordinate multiple agents and tasks for complex workflows. Orchestrate subagents, manage dependencies, handle parallel execution, and ensure successful comp...

Security Scan

The skill's orchestration instructions look reasonable, but unexplained environment and install requirements (BRAVE_API_KEY and an npm 'async' binary) and missing source/homepage make the package incoherent and potentially risky.

Purpose & Capability

The skill claims to coordinate subagents and manage workflows — that aligns with the SKILL.md instructions. However, the declared required environment variable (BRAVE_API_KEY) is unrelated to orchestration and is never referenced in the instructions. The install spec asks for an npm package 'async' and declares it creates a binary named 'async' (the npm 'async' package is a JS library, not a CLI binary). These requirements do not match the stated purpose and are disproportionate or unexplained.

Instruction Scope

The SKILL.md is instruction-only and stays within orchestration concerns (spawn/monitor/kill subagents, dependency resolution, templates). It is quite high-level and grants broad discretion to spawn and manage subagents (including 'self-evolution' uses), which is powerful but consistent with an orchestration skill. The instructions do not reference BRAVE_API_KEY, curl/jq usage, or any external endpoints, and they are vague in ways that could enable wide-ranging agent behavior if the agent platform honors commands like sessions_spawn and subagents kill/steer.

Install Mechanism

An npm install entry is present for package 'async' that purportedly creates a binary 'async'. This is inconsistent: 'async' on npm is a JS library (not a known CLI), and the skill contains no code files that would need that dependency. Installing arbitrary npm packages can introduce supply-chain risk; here the install requirement appears unnecessary or malformed.

Credentials

The skill requires BRAVE_API_KEY but the SKILL.md contains no instructions that use Brave or any external search/API requiring that key. Requiring a secret-like environment variable without justification is disproportionate. No primary credential is declared, and no other env/config paths are requested.

Persistence & Privilege

The skill does not request always:true, does not declare system config paths, and is user-invocable only. That is a normal privilege profile. Note: the functional ability to spawn and manage subagents (per the instructions) is powerful — review platform-level permissions for spawning agents before enabling.

What to consider before installing

This skill's described orchestration features are plausible, but several inconsistencies suggest caution: - Ask the publisher (or repository) why BRAVE_API_KEY is required and what it's used for; do not provide sensitive tokens until that is explained. - Confirm why an npm 'async' package and an 'async' binary are installed — that package is normally a JS library, not a CLI. If you must install it, review the exact package and its maintainer and audit the package contents in a sandbox first. - Because the skill can spawn and steer subagents, run it in a restricted/sandboxed environment and limit its privileges on first use. - Prefer skills with a verifiable source/homepage and code you can inspect; this skill has no source URL or code files. If you cannot get a clear explanation for the BRAVE_API_KEY and the odd install spec, treat this skill as untrusted and avoid installing it or set it up in an isolated test environment only.

Coordinate multiple agents and tasks for complex workflows.

When to Use

• Multi-step operations requiring coordination
• Parallel execution of independent tasks
• Complex workflows with dependencies
• Orchestrating subagents for large projects

Core Capabilities

1. Task Coordination

• Break down complex tasks into manageable steps
• Manage dependencies between tasks
• Coordinate parallel execution
• Handle task sequencing and scheduling

2. Agent Orchestration

• Spawn and manage multiple subagents
• Route tasks to appropriate agents
• Monitor progress and handle failures
• Aggregate results from multiple sources

3. Workflow Management

• Define workflow patterns and templates
• Implement error handling and recovery
• Manage state and progress tracking
• Coordinate handoffs between agents

4. Dependency Resolution

• Analyze task dependencies
• Create execution order
• Handle conditional execution
• Manage resource conflicts

Orchestration Patterns

1. Sequential Execution

Task A → Task B → Task C

2. Parallel Execution

Task A, Task B, Task C → Aggregate

3. Pipeline Processing

Input → Task A → Task B → Task C → Output

4. Supervisor Pattern

Coordinator → Multiple Subagents → Results

5. Event-Driven Processing

Event → Trigger → Response → Next Event

Quick Actions

• orchestrate [workflow] - Execute complex workflow
• parallel [tasks] - Run tasks in parallel
• pipeline [steps] - Chain tasks in sequence
• supervise [agents] - Manage multiple agents
• dependencies [tasks] - Analyze and resolve dependencies

Usage Examples

"Orchestrate a complete research project with multiple agents"
"Run these tasks in parallel and combine results"
"Create a pipeline for content creation from research to publication"
"Supervise a team of agents working on different aspects"
"Analyze dependencies and create execution order"

Workflow Templates

Research Project

1. Research Topic → Research Agent
2. Data Collection → Data Agent
3. Analysis → Analysis Agent
4. Report Generation → Writing Agent
5. Review → QA Agent

Content Creation

1. Topic Research → Research Agent
2. Outline Creation → Writing Agent
3. Draft Writing → Writing Agent
4. Editing → Editing Agent
5. Publication → Publishing Agent

Software Development

1. Requirements → Analysis Agent
2. Design → Design Agent
3. Implementation → Coding Agent
4. Testing → QA Agent
5. Deployment → Deployment Agent

Agent Management

Spawning Agents

sessions_spawn({ task: "specific task", label: "agent-name", mode: "run" })

Monitoring Progress

subagents list

Handling Failures

subagents kill [agent-id]
subagents steer [agent-id] "new instructions"

Dependency Resolution

Types of Dependencies

• Data Dependencies: Task B needs output from Task A
• Resource Dependencies: Tasks sharing same resources
• Order Dependencies: Tasks must run in specific order
• Conditional Dependencies: Task runs only if condition met

Resolution Process

1. Identify all dependencies
2. Create dependency graph
3. Find topological sort
4. Execute in dependency order
5. Handle conflicts and cycles

Error Handling

Common Failure Scenarios

• Agent Failure: Subagent crashes or times out
• Dependency Failure: Required task fails
• Resource Conflict: Multiple agents need same resource
• Network Issues: API calls fail or timeout

Recovery Strategies

• Retry: Attempt failed task again
• Alternative: Use different approach or agent
• Skip: Continue without failed task
• Rollback: Undo previous steps

State Management

Progress Tracking

• Track completed tasks
• Monitor current execution
• Record task results
• Maintain workflow state

Checkpointing

• Save progress at key points
• Enable restart from checkpoints
• Maintain consistency across failures

Communication Patterns

Parent → Child

/sessions_send [agent-id] "instructions"

Child → Parent

Auto-announce results
Reply with findings
Report errors and status

Agent → Agent

Share data through files
Coordinate via shared state
Trigger other agents

Performance Optimization

Parallel Execution

• Identify independent tasks
• Run in parallel when possible
• Aggregate results efficiently

Resource Management

• Monitor agent resource usage
• Balance load across agents
• Avoid resource conflicts

Efficiency Metrics

• Task completion time
• Resource utilization
• Error rates
• Success rates

Safety Considerations

Agent Limits

• Max 10 concurrent subagents
• Max 2 levels of nesting
• 10-minute timeout per agent
• Automatic cleanup

Data Integrity

• Validate task inputs/outputs
• Maintain consistency
• Handle partial failures
• Ensure atomic operations

Advanced Patterns

1. Hierarchical Orchestration

Main Coordinator → Team Coordinators → Individual Agents

2. Dynamic Work Allocation

Assign tasks based on agent capabilities
Reassign if agent fails
Balance load dynamically

3. Event-Driven Workflows

Event → Trigger → Agent → Result → Next Event

4. Adaptive Planning

Plan → Execute → Monitor → Adjust → Repeat

Integration with Other Skills

Self-Evolution

• Use for complex self-improvement tasks
• Coordinate multiple evolution agents
• Manage long-term capability building

Analysis Skills

• Orchestrate research projects
• Coordinate data analysis
• Manage multi-step investigations

Content Creation

• Coordinate content production pipelines
• Manage multi-agent content creation
• Orchestrate publication workflows

Quick Reference

Common Commands

# List running agents
subagents list

# Kill failed agent
subagents kill [id]

# Send instructions
sessions_send [agent-id] "message"

# Spawn new agent
sessions_spawn({ task: "task", label: "name", mode: "run" })

Workflow Examples

# Research project
orchestrate "research-project" with agents: research, analysis, writing

# Content pipeline
pipeline "content-creation" with steps: research, outline, draft, edit, publish

# Software development
supervise "dev-team" with agents: analysis, design, coding, testing, deployment

Best Practices

1. Start Simple: Begin with sequential execution
2. Add Parallelism: Identify independent tasks
3. Handle Failures: Implement robust error handling
4. Monitor Progress: Track execution and results
5. Optimize Performance: Balance load and resources

Success Metrics

• Task completion rate
• Execution time efficiency
• Resource utilization
• Error recovery effectiveness
• Overall workflow success

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Remember: Good orchestration makes complex tasks manageable and reliable.