team-polish▌
Donchitos/Claude-Code-Game-Studios · updated Apr 16, 2026
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### Team Polish
- ›description: "Orchestrate the polish team: coordinates performance-analyst, technical-artist, sound-designer, and qa-tester to optimize, polish, and harden a feature or area for release quality."
- ›argument-hint: "[feature or area to polish]"
- ›allowed-tools: Read, Glob, Grep, Write, Edit, Bash, Task, AskUserQuestion, TodoWrite
| name | team-polish |
| description | "Orchestrate the polish team: coordinates performance-analyst, technical-artist, sound-designer, and qa-tester to optimize, polish, and harden a feature or area for release quality." |
| argument-hint | "[feature or area to polish]" |
| user-invocable | true |
| allowed-tools | Read, Glob, Grep, Write, Edit, Bash, Task, AskUserQuestion, TodoWrite |
If no argument is provided, output usage guidance and exit without spawning any agents:
Usage:
/team-polish [feature or area]— specify the feature or area to polish (e.g.,combat,main menu,inventory system,level-1). Do not useAskUserQuestionhere; output the guidance directly.
When this skill is invoked with an argument, orchestrate the polish team through a structured pipeline.
Decision Points: At each phase transition, use AskUserQuestion to present
the user with the subagent's proposals as selectable options. Write the agent's
full analysis in conversation, then capture the decision with concise labels.
The user must approve before moving to the next phase.
Team Composition
- performance-analyst — Profiling, optimization, memory analysis, frame budget
- engine-programmer — Engine-level bottlenecks: rendering pipeline, memory, resource loading (invoke when performance-analyst identifies low-level root causes)
- technical-artist — VFX polish, shader optimization, visual quality
- sound-designer — Audio polish, mixing, ambient layers, feedback sounds
- tools-programmer — Content pipeline tool verification, editor tool stability, automation fixes (invoke when content authoring tools are involved in the polished area)
- qa-tester — Edge case testing, regression testing, soak testing
How to Delegate
Use the Task tool to spawn each team member as a subagent:
subagent_type: performance-analyst— Profiling, optimization, memory analysissubagent_type: engine-programmer— Engine-level fixes for rendering, memory, resource loadingsubagent_type: technical-artist— VFX polish, shader optimization, visual qualitysubagent_type: sound-designer— Audio polish, mixing, ambient layerssubagent_type: tools-programmer— Content pipeline and editor tool verificationsubagent_type: qa-tester— Edge case testing, regression testing, soak testing
Always provide full context in each agent's prompt (target feature/area, performance budgets, known issues). Launch independent agents in parallel where the pipeline allows it (e.g., Phases 3 and 4 can run simultaneously).
Pipeline
Phase 1: Assessment
Delegate to performance-analyst:
- Profile the target feature/area using
/perf-profile - Identify performance bottlenecks and frame budget violations
- Measure memory usage and check for leaks
- Benchmark against target hardware specs
- Output: performance report with prioritized optimization list
Phase 2: Optimization
Delegate to performance-analyst (with relevant programmers as needed):
- Fix performance hotspots identified in Phase 1
- Optimize draw calls, reduce overdraw
- Fix memory leaks and reduce allocation pressure
- Verify optimizations don't change gameplay behavior
- Output: optimized code with before/after metrics
If Phase 1 identified engine-level root causes (rendering pipeline, resource loading, memory allocator), delegate those fixes to engine-programmer in parallel:
- Optimize hot paths in engine systems
- Fix allocation pressure in core loops
- Output: engine-level fixes with profiler validation
Phase 3: Visual Polish (parallel with Phase 2)
Delegate to technical-artist:
- Review VFX for quality and consistency with art bible
- Optimize particle systems and shader effects
- Add screen shake, camera effects, and visual juice where appropriate
- Ensure effects degrade gracefully on lower settings
- Output: polished visual effects
Phase 4: Audio Polish (parallel with Phase 2)
Delegate to sound-designer:
- Review audio events for completeness (are any actions missing sound feedback?)
- Check audio mix levels — nothing too loud or too quiet relative to the mix
- Add ambient audio layers for atmosphere
- Verify audio plays correctly with spatial positioning
- Output: audio polish list and mixing notes
Phase 5: Hardening
Delegate to qa-tester:
- Test all edge cases: boundary conditions, rapid inputs, unusual sequences
- Soak test: run the feature for extended periods checking for degradation
- Stress test: maximum entities, worst-case scenarios
- Regression test: verify polish changes haven't broken existing functionality
- Test on minimum spec hardware (if available)
- Output: test results with any remaining issues
Phase 6: Sign-off
- Collect results from all team members
- Compare performance metrics against budgets
- Report: READY FOR RELEASE / NEEDS MORE WORK
- List any remaining issues with severity and recommendations
Error Recovery Protocol
If any spawned agent (via Task) returns BLOCKED, errors, or cannot complete:
- Surface immediately: Report "[AgentName]: BLOCKED — [reason]" to the user before continuing to dependent phases
- Assess dependencies: Check whether the blocked agent's output is required by subsequent phases. If yes, do not proceed past that dependency point without user input.
- Offer options via AskUserQuestion with choices:
- Skip this agent and note the gap in the final report
- Retry with narrower scope
- Stop here and resolve the blocker first
- Always produce a partial report — output whatever was completed. Never discard work because one agent blocked.
Common blockers:
- Input file missing (story not found, GDD absent) → redirect to the skill that creates it
- ADR status is Proposed → do not implement; run
/architecture-decisionfirst - Scope too large → split into two stories via
/create-stories - Conflicting instructions between ADR and story → surface the conflict, do not guess
File Write Protocol
All file writes (performance reports, test results, evidence docs) are delegated to sub-agents spawned via Task. Each sub-agent enforces the "May I write to [path]?" protocol. This orchestrator does not write files directly.
Output
A summary report covering: performance before/after metrics, visual polish changes, audio polish changes, test results, and release readiness assessment.
Next Steps
- If READY FOR RELEASE: run
/release-checklistfor the final pre-release validation. - If NEEDS MORE WORK: schedule remaining issues in
/sprint-plan updateand re-run/team-polishafter fixes. - Run
/gate-checkfor a formal phase gate verdict before handing off to release.
How to use team-polish on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add team-polish
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches team-polish from GitHub repository Donchitos/Claude-Code-Game-Studios and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate team-polish. Access the skill through slash commands (e.g., /team-polish) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★43 reviews- ★★★★★Neel Abebe· Dec 24, 2024
Keeps context tight: team-polish is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Shikha Mishra· Dec 20, 2024
team-polish has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Alexander Sanchez· Dec 16, 2024
team-polish reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kofi Kapoor· Dec 4, 2024
Registry listing for team-polish matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Anika Singh· Nov 23, 2024
Solid pick for teams standardizing on skills: team-polish is focused, and the summary matches what you get after install.
- ★★★★★Nikhil Bansal· Nov 7, 2024
team-polish is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Anika Harris· Nov 3, 2024
team-polish has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aanya Taylor· Oct 26, 2024
Useful defaults in team-polish — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Min Menon· Oct 22, 2024
Keeps context tight: team-polish is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Daniel Abbas· Oct 14, 2024
We added team-polish from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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