parallel-task-spark
Only to be triggered by explicit /parallel-task-spark commands.
Best use case
parallel-task-spark is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Only to be triggered by explicit /parallel-task-spark commands.
Teams using parallel-task-spark should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/parallel-task-spark/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How parallel-task-spark Compares
| Feature / Agent | parallel-task-spark | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Only to be triggered by explicit /parallel-task-spark commands.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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. Examine working plan and any relevant or dependent files
2. Implement changes for all acceptance criteria
3. Keep work **atomic and committable**
4. For each file: read first, edit carefully, preserve formatting
5. Run validation if feasible
6. **ALWAYS mark completed tasks IN THE *-plan.md file AS SOON AS YOU COMPLETE IT!** and update with:
- Concise work log
- Files modified/created
- Errors or gotchas encountered
7. Commit your work
- Note: There are other agents working in parallel to you, so only stage and commit the files you worked on. NEVER PUSH. ONLY COMMIT.
8. Double Check that you updated the *-plan.md file and committed your work before yielding
9. Return summary of:
- Files modified/created
- Changes made
- How criteria are satisfied
- Validation performed or deferred
## Important
- Be careful with paths
- Stop and describe blockers if encountered
- Focus on this specific task
```
Ensure that the agent marked its task complete before moving on to the next task or set of tasks.
### Step 4: Check and Validate.
After subagents complete their work:
1. Inspect their outputs for correctness and completeness.
2. Validate the results against the expected outcomes.
3. If the task is truly completed correctly, ENSURE THAT TASK WAS MARKED COMPLETE WITH LOGS.
4. If a task was not successful, have the agent retry or escalate the issue.
5. Ensure that that wave of work has been committed to github before moving on to the next wave of tasks.
### Step 5: Repeat
1. Review the plan again to see what new set of unblocked tasks are available.
2. Continue launching unblocked tasks in parallel until plan is done.
3. Repeat the process until *all** tasks are both complete, validated, and working without errors.
## Error Handling
- Task subset not found: List available task IDs
- Parse failure: Show what was tried, ask for clarification
## Example Usage
```
'Implement the plan using parallel task skill'
/parallel-task-spark plan.md
/parallel-task-spark ./plans/auth-plan.md T1 T2 T4
/parallel-task-spark user-profile-plan.md --tasks T3 T7
```
## Execution Summary Template
```markdown
# Execution Summary
## Tasks Assigned: [N]
### Completed
- Task [ID]: [Name] - [Brief summary]
### Issues
- Task [ID]: [Name]
- Issue: [What went wrong]
- Resolution: [How resolved or what's needed]
### Blocked
- Task [ID]: [Name]
- Blocker: [What's preventing completion]
- Next Steps: [What needs to happen]
## Overall Status
[Completion summary]
## Files Modified
[List of changed files]
## Next Steps
[Recommendations]
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