Orchestrates parallel task execution across up to 12 concurrent Sparky subagents using a rolling pool scheduler.
Create detailed user stories, acceptance criteria, and feature specs
Example: Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example: Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example: Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example: Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Submit your Claude Code skill and start earning
epx add am-will/codex-skills --skill super-swarm-sparkCompatible with
Supported agents
Parses markdown plan files, extracts task definitions, and launches subagents continuously as slots open without waiting for batch completion
Maintains canonical file paths and naming constraints across parallel tasks to prevent filename drift and cross-task conflicts
Validates each subagent result, updates the plan file with completion logs, and immediately schedules the
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsuper-swarm-sparkExecute the skills CLI command in your project's root directory to begin installation:
epx add am-will/codex-skills --skill super-swarm-sparkFetches super-swarm-spark from am-will/codex-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/super-swarm-spark
Restart Cursor to activate super-swarm-spark. Access via /super-swarm-sparkin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Time estimate: 30-60 minutes to see productivity improvements
Prerequisites
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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I recommend super-swarm-spark for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: super-swarm-spark is focused, and the summary matches what you get after install.
super-swarm-spark fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
super-swarm-spark has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: super-swarm-spark is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for super-swarm-spark matched our evaluation — installs cleanly and behaves as described in the markdown.
super-swarm-spark reduced setup friction for our internal harness; good balance of opinion and flexibility.
super-swarm-spark is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
super-swarm-spark is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
super-swarm-spark reduced setup friction for our internal harness; good balance of opinion and flexibility.
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