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team-polish团队打磨

Agent Skill

team-polish 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,035

周安装

44

GitHub Stars

16,796

下载量

363
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:team-polish(团队打磨)
来源仓库:https://github.com/donchitos/claude-code-game-studios
仓库路径:skills/team-polish
安装命令:
npx skills add https://github.com/donchitos/claude-code-game-studios --skill team-polish
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/donchitos/claude-code-game-studios --skill team-polish

简介

team-polish 用于处理 GitHub 仓库、Issue、Pull Request 等协作数据。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中优化代码或协作流程的场景。
  • 通过 npx skills add 命令安装,功能细节需查阅原始项目文档。
  • 安装前建议核实权限、维护状态及是否执行系统命令或读写文件。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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 use AskUserQuestion here; 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 analysis
  • subagent_type: engine-programmer — Engine-level fixes for rendering, memory, resource loading
  • subagent_type: technical-artist — VFX polish, shader optimization, visual quality
  • subagent_type: sound-designer — Audio polish, mixing, ambient layers
  • subagent_type: tools-programmer — Content pipeline and editor tool verification
  • subagent_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:

  1. Surface immediately: Report "[AgentName]: BLOCKED — [reason]" to the user before continuing to dependent phases
  2. 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.
  3. 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

  1. 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-decision first
  • 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-checklist for the final pre-release validation.
  • If NEEDS MORE WORK: schedule remaining issues in /sprint-plan update and re-run /team-polish after fixes.
  • Run /gate-check for a formal phase gate verdict before handing off to release.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

40.29%
按下载量换算146

Claude

29.06%
按下载量换算105

Cursor

18.33%
按下载量换算67

Gemini CLI

9.5%
按下载量换算34

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/donchitos/claude-code-game-studios --skill team-polish 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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