df:execute-objective

Name: df:execute-objective
Availability: InStock
Author: AO-Cyber-Systems

Execute objective jobs with wave-based parallelism and dependency-aware scheduling.

Updated Feb 6, 2026

Search Tags:#workflow #planning #subagents #parallel #orchestrator #execute #objective

Ready to run

npx skills add https://github.com/AO-Cyber-Systems/devflow-claude --skill df-execute-objective

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: df:execute-objective
Source: https://github.com/AO-Cyber-Systems/devflow-claude/tree/main/skills/df-execute-objective
Command: npx skills add https://github.com/AO-Cyber-Systems/devflow-claude --skill df-execute-objective

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates and coordinates multiple tasks within a defined objective, reducing manual coordination, drift, and context rot by running jobs in waves and collecting results in a unified workflow.

Core Features & Use Cases

Wave-based parallel execution: discovers plans, analyzes dependencies, groups work into execution waves, and spawns subagents to execute tasks concurrently while maintaining global progress and state.
Objective-driven automation: suitable for building, running, or executing a planned objective with clear gating, verification, and state updates.
Context-aware orchestration: loads full execute-job context per subagent and respects checkpoints and routing requirements for robust fault tolerance.

Quick Start

Start the df:execute-objective workflow to run all jobs in your current objective and observe wave-based progress and results.

Frequently Asked Questions about df:execute-objective

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How does wave-based parallel execution coordinate subagents for complex project workflows?▼

Wave-based parallel execution coordinates subagents by discovering plans, analyzing dependencies, and grouping tasks into execution waves that run concurrently. This dependency-aware scheduling ensures multi-agent coordination while maintaining global progress and state management across the objective.

How do I orchestrate multiple jobs within a defined objective to reduce manual coordination and context rot?▼

You orchestrate multiple jobs by running them in waves and collecting results in a unified workflow. This approach reduces manual coordination, drift, and context rot by applying dependency-aware scheduling and spawning subagents to execute tasks concurrently.

Can I use dependency-aware scheduling for multi-agent coordination in large projects?▼

Yes, dependency-aware scheduling supports multi-agent coordination for large projects by analyzing task dependencies, grouping work into execution waves, and spawning subagents concurrently. It maintains global progress and state management while respecting checkpoints and routing requirements.

What is the best way to execute planned objectives with clear gating and verification?▼

The best way to execute planned objectives with clear gating and verification is using an end-to-end workflow that implements plan discovery, dependency analysis, wave grouping, and subagent execution. This objective-driven automation ensures robust fault tolerance through context-aware orchestration.

How does context-aware orchestration handle fault tolerance during subagent execution?▼

Context-aware orchestration handles fault tolerance by loading full execute-job context per subagent and respecting checkpoints and routing requirements. This ensures robust execution even when issues arise, maintaining state updates and verification throughout the workflow.

Why does dependency analysis matter when grouping tasks into execution waves?▼

Dependency analysis matters because it determines which tasks can run concurrently in the same wave and which must wait for dependencies to complete. This grouping enables parallel execution while preventing conflicts and ensuring proper task ordering across the objective workflow.