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team-combat团队作战

Agent Skill

team-combat 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

1,063

周安装

43

GitHub Stars

16,590

下载量

334
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-combat(团队作战)
来源仓库:https://github.com/donchitos/claude-code-game-studios
仓库路径:skills/team-combat
安装命令:
npx skills add https://github.com/donchitos/claude-code-game-studios --skill team-combat
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-combat

简介

team-combat 用于处理 GitHub 仓库和协作信息。

  • 适合围绕仓库状态、代码变更和协作事项整理。
  • 可结合来源仓库和原始 README 核验具体功能。
  • 安装前建议确认权限范围和维护状态。team-combat 属于前端设计类 Skill,可作为该场景下的辅助能力补充。
  • 注意是否会触发写入操作或访问私有仓库。

SKILL.md

Argument check: If no combat feature description is provided, output:

"Usage: /team-combat [combat feature description] — Provide a description of the combat feature to design and implement (e.g., melee parry system, ranged weapon spread)." Then stop immediately without spawning any subagents or reading any files.

When this skill is invoked with a valid argument, orchestrate the combat 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

  • game-designer — Design the mechanic, define formulas and edge cases
  • gameplay-programmer — Implement the core gameplay code
  • ai-programmer — Implement NPC/enemy AI behavior for the feature
  • technical-artist — Create VFX, shader effects, and visual feedback
  • sound-designer — Define audio events, impact sounds, and ambient combat audio
  • engine specialist (primary) — Validate architecture and implementation patterns are idiomatic for the engine (read from .claude/docs/technical-preferences.md Engine Specialists section)
  • qa-tester — Write test cases and validate the implementation

How to Delegate

Use the Task tool to spawn each team member as a subagent:

  • subagent_type: game-designer — Design the mechanic, define formulas and edge cases
  • subagent_type: gameplay-programmer — Implement the core gameplay code
  • subagent_type: ai-programmer — Implement NPC/enemy AI behavior
  • subagent_type: technical-artist — Create VFX, shader effects, visual feedback
  • subagent_type: sound-designer — Define audio events, impact sounds, ambient audio
  • subagent_type: [primary engine specialist] — Engine idiom validation for architecture and implementation
  • subagent_type: qa-tester — Write test cases and validate implementation

Always provide full context in each agent's prompt (design doc path, relevant code files, constraints). Launch independent agents in parallel where the pipeline allows it (e.g., Phase 3 agents can run simultaneously).

Pipeline

Phase 1: Design

Delegate to game-designer:

  • Create or update the design document in design/gdd/ covering: mechanic overview, player fantasy, detailed rules, formulas with variable definitions, edge cases, dependencies, tuning knobs with safe ranges, and acceptance criteria
  • Output: completed design document

Phase 2: Architecture

Delegate to gameplay-programmer (with ai-programmer if AI is involved):

  • Review the design document
  • Design the code architecture: class structure, interfaces, data flow
  • Identify integration points with existing systems
  • Output: architecture sketch with file list and interface definitions

Then spawn the primary engine specialist to validate the proposed architecture:

  • Is the class/node/component structure idiomatic for the pinned engine? (e.g., Godot node hierarchy, Unity MonoBehaviour vs DOTS, Unreal Actor/Component design)
  • Are there engine-native systems that should be used instead of custom implementations?
  • Any proposed APIs that are deprecated or changed in the pinned engine version?
  • Output: engine architecture notes — incorporate into the architecture before Phase 3 begins

Phase 3: Implementation (parallel where possible)

Delegate in parallel:

  • gameplay-programmer: Implement core combat mechanic code
  • ai-programmer: Implement AI behaviors (if the feature involves NPC reactions)
  • technical-artist: Create VFX and shader effects
  • sound-designer: Define audio event list and mixing notes

Phase 4: Integration

  • Wire together gameplay code, AI, VFX, and audio
  • Ensure all tuning knobs are exposed and data-driven
  • Verify the feature works with existing combat systems

Phase 5: Validation

Delegate to qa-tester:

  • Write test cases from the acceptance criteria
  • Test all edge cases documented in the design
  • Verify performance impact is within budget
  • File bug reports for any issues found

Phase 6: Sign-off

  • Collect results from all team members
  • Report feature status: COMPLETE / NEEDS WORK / BLOCKED
  • List any outstanding issues and their assigned owners

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 (design documents, implementation files, test cases) 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: design completion status, implementation status per team member, test results, and any open issues.

Verdict: COMPLETE — combat feature designed, implemented, and validated. Verdict: BLOCKED — one or more phases could not complete; partial report produced with unresolved items listed.

Next Steps

  • Run /code-review on the implemented combat code before closing stories.
  • Run /balance-check to validate combat formulas and tuning values.
  • Run /team-polish if VFX, audio, or performance polish is needed.

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

40.39%
按下载量换算135

Claude

29.91%
按下载量换算100

Cursor

17.71%
按下载量换算59

Gemini CLI

9.32%
按下载量换算31

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-combat 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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