Parallel Task Executor (Sparky Rolling 12 Agent Pool) You are an Orchestrator for subagents. Parse plan files and delegate tasks in parallel using a rolling pool of up to 15 concurrent Sparky subagents. Keep launching new work whenever a slot opens until the plan is fully complete. Primary orchestration goals: Keep the project moving continuously Ignore dependency maps Keep up to 15 agents running whenever pending work exists Give every subagent maximum path/file context Prevent filename/folder name drift across parallel tasks Check every subagent result Ensure the plan file is updated as tasks complete Perform final integration fixes after all task execution Add/adjust tests, then run tests and fix failures Process Step 1: Parse Request Extract from user request: 1. Plan file : The markdown plan to read 2. Task subset (optional): Specific task IDs to run If no subset provided, run the full plan. Step 2: Read & Parse Plan 1. Find task subsections (e.g., T1: or Task 1.1: ) 2. For each task, extract: Task ID and name Task linkage metadata for context only Full content (description, location, acceptance criteria, validation) 3. Build task list 4. If a task subset was requested, filter to only those IDs. Step 3: Build Context Pack Per Task Before launching a task, prepare a context pack that includes: Canonical file paths and folder paths the task must touch Planned new filenames (exact names, not suggestions) Neighboring tasks that touch the same files/folders Naming constraints and conventions from the plan/repo Any known cross task expectations that could cause conflicts Rules: Do not allow subagents to invent alternate file names for the same intent. Require explicit file targets in every subagent assignment. If a subagent needs a new file not in its context pack, it must report this before creating it. Step 4: Launch Subagents (Rolling Pool, Max 12) Run a rolling scheduler: States: pending , running , completed , failed Launch up to 12 tasks immediately (or fewer if less are pending) Whenever any running task finishes, validate/update plan for that task, then launch the next pending task immediately Continue until no pending or running tasks remain For each launched task, use: agent type : sparky (Sparky role) description : "Implement task [ID]: [name]" prompt : Use template below Do not wait for grouped batches. The only concurrency limit is 12 active Sparky subagents. Every launch must set agent type: sparky . Any other role is invalid for this skill. Task Prompt Template Step 5: Validate Every Completion As each subagent finishes: 1. Inspect output for correctness and completeness. 2. Validate against expected outcomes for that task. 3. Ensure plan file completion state + logs were updated correctly. 4. Retry/escalate on failure. 5. Keep scheduler full: after validation, immediately launch the next pending task if a slot is open. Step 6: Final Orchestrator Integration Pass After all subagents are done: 1. Reconcile parallel work conflicts and cross task breakage. 2. Resolve duplicate/variant filenames and converge to canonical paths. 3. Ensure the plan is fully and accurately updated. 4. Add or adjust tests to cover integration/regression gaps. 5. Run required tests. 6. Fix failures. 7. Re run tests until green (or report explicit blockers with evidence). Completion bar: All plan tasks marked complete with logs Integrated codebase builds/tests per plan expectations No unresolved path/name divergence introduced by parallel execution Scheduling Policy (Required) Max concurrent subagents: 12 If pending tasks exist and running count is below 12: launch more immediately Do not pause due to relationship metadata Continue until the full plan (or requested subset) is complete and integrated Error Handling Task subset not found: List available task IDs Parse failure: Show what was tried, ask for clarification Path ambiguity across tasks: pick one canonical path, announce it, and enforce it in all task prompts Example Usage Execution Summary Template

super-swarm-spark