
Parallel Task Spark
Orchestrate parallel Sparky subagents from a markdown implementation plan, respecting task dependencies and updating plan logs after each wave.
Overview
parallel-task-spark is an agent skill most often used in Build (pm) (also Ship testing, Operate iterate) that parses markdown plans and runs dependency-ordered parallel Sparky subagents until every task is done and logge
Install
npx skills add https://github.com/am-will/codex-skills --skill parallel-task-sparkWhat is this skill?
- Explicit /parallel-task-spark command gate—does not run unless user invokes it
- Parses plan tasks from ### T1: or ### Task 1.1: headings with depends_on metadata
- Launches only Sparky-role subagents for unblocked tasks in parallel waves
- Optional task-subset filter still pulls required dependency chain
- Updates plan documentation with logs after each completed task
- 4-step process: parse request, read plan, launch subagents, loop until complete
Adoption & trust: 1.1k installs on skills.sh; 941 GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You have a detailed markdown plan but one agent executes tasks serially, wasting time on independent workstreams.
Who is it for?
Power users with structured T1/T2 plans, explicit depends_on fields, and willingness to supervise multi-agent output.
Skip if: Ad-hoc one-shot prompts, plans without task IDs or dependency metadata, or workflows that forbid parallel subagents.
When should I use this skill?
Only when the user explicitly issues a /parallel-task-spark command with a plan file path (optional task ID subset).
What do I get? / Deliverables
Blocked-aware parallel subagent waves complete plan tasks in order while the plan file gains per-task completion logs.
- Completed plan tasks via parallel subagents
- Updated plan logs per finished task
- Dependency-respecting execution waves
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Plan execution orchestration sits where specs become parallel agent work—the canonical shelf is build PM/agent coordination. PM subphase covers breaking plans into tracked tasks and delegating implementation waves to agents.
Where it fits
Run ten frontend and API tasks from an approved plan once shared types land in T1.
Parallelize independent endpoint implementations after the orchestrator confirms schema migration tasks completed.
Execute a fix-list plan where unrelated test repairs share no depends_on edges.
Burn down a maintenance plan with parallel doc and config updates.
How it compares
Orchestration workflow for plan files—not a single-task coder skill or an MCP server.
Common Questions / FAQ
Who is parallel-task-spark for?
Solo builders and small teams running Codex or compatible agents who already maintain markdown implementation plans and want Sparky workers in parallel.
When should I use parallel-task-spark?
In Build when executing a multi-task spec; in Ship when regression-fix plans list parallel-safe tasks; in Operate when iteration plans bundle independent chores—always via /parallel-task-spark.
Is parallel-task-spark safe to install?
Parallel agents can touch many files quickly; review Security Audits on this page, narrow task subsets, and inspect diffs before merging.
SKILL.md
READMESKILL.md - Parallel Task Spark
# Parallel Task Executor (Sparky) You are an Orchestrator for subagents. Use orchestration mode to parse plan files and delegate tasks to parallel Sparky subagents using task dependencies, in a loop, until all tasks are completed. Your role is to ensure that subagents are launched in the correct order (in waves), and that they complete their tasks correctly, as well as ensure the plan docs are updated with logs after each task is completed. ## 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 - **depends_on** list (from `- **depends_on**: [...]`) - Full content (description, location, acceptance criteria, validation) 3. Build task list 4. If a task subset was requested, filter the task list to only those IDs and their required dependencies. ### Step 3: Launch Subagents For each **unblocked** task, launch subagent with: - **agent_type**: `sparky` (Sparky role) - **description**: "Implement task [ID]: [name]" - **prompt**: Use template below Launch all unblocked tasks in parallel, and use only Sparky-role subagents. A task is unblocked if all IDs in its depends_on list are complete. Every launch must set `agent_type: sparky`. Any other role is invalid for this skill. ### Task Prompt Template ``` You are implementing a specific task from a development plan. ## Context - Plan: [filename] - Goals: [relevant overview from plan] - Dependencies: [prerequisites for this task] - Related tasks: [tasks that depend on or are depended on by this task] - Constraints: [risks from plan] ## Your Task **Task [ID]: [Name]** Location: [File paths] Description: [Full description] Acceptance Criteria: [List from plan] Validation: [Tests or verification from plan] ## Instructions - Use the `sparky` agent role for this task; do not use any other role. 1. Read the working plan and fully understand this task before coding. 2. Read all relevant files first, then do targeted codebase research (related modules, tests, call sites, and dependencies) to confirm the approach. 3. Default to TDD RED phase first using a `tdd_test_writer` subagent: - Pass task context and acceptance criteria. - Require tests-only edits. - Require command output proving the new/updated tests fail for the expected behavior gap. - If the task is not a good TDD candidate, explicitly record `reason_not_testable` and define alternative verification evidence (for example `manual_check`, `static_check`, or `runtime_check`) with an exact command or concrete validation steps. 4. Review RED-phase tests (or approved non-testable verification plan) as the implementation contract. Do not weaken or remove tests unless requirements changed. 5. Implement production changes for all acceptance criteria. 6. Run validation: - For testable tasks, run the exact new/updated test command(s) until GREEN (passing). - For non-testable tasks, run the agreed alternative verification and capture evidence. - Run any additional validation steps from the plan if feasible. 7. Commit your work. - Stage only files for this task because other agents are working in parallel. - NEVER PUSH. ONLY COMMIT. 8. After the commit, update the `*-plan.md` task entry with: - Completion status - Concise work log - Files modified/created - Errors or gotchas encountered 9. Return summary of: - Files modified/created - Changes made - How criteria are satisfied - Verification evidence: RED -> GREEN or documented non-testable alternative - Validation performed or deferred ## Important - Be careful with paths - Stop and describe blockers if encountered - F