Claude Code Game Studios is a setup that organizes Claude Code into a coordinated game-development team of specialized AI agents. It supports game projects across design, programming, art, audio, narrative, quality assurance, and production, with skills and workflows for coordinating that work.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/donchitos/claude-code-game-studios/team-combatnpx skills add Donchitos/Claude-Code-Game-Studios --skill team-combatgit clone --depth 1 https://github.com/Donchitos/Claude-Code-Game-StudiosWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/donchitos/claude-code-game-studios/team-combat)<a href="https://agentmods.dev/skills/donchitos/claude-code-game-studios/team-combat"><img src="https://agentmods.dev/badge/skills/donchitos/claude-code-game-studios/team-combat.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00050 | $0.01688 |
| Opus 5 | $0.00025 | $0.00844 |
| Sonnet 5 | $0.00010 | $0.00338 |
| Haiku 4.5 | $0.00005 | $0.00169 |
Grade A, and why
team-combat scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- team-combat — 100% identical, 3 lines differ
- team-combat — 89% identical, 25 lines differ
- team-combat — 88% identical, 33 lines differ
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
Phase 0: Resolve Review Mode
- If
--review [mode]was passed as an argument, use that mode. - Else read
production/review-mode.txt— use whatever is written there. - Else default to
lean.
Modes:
full— spawn all director and lead gates as describedlean— skip director gates unless they are PHASE-GATE type (CD-PHASE-GATE, TD-PHASE-GATE, PR-PHASE-GATE, AD-PHASE-GATE)solo— skip all director gate spawning entirely; run the skill without any agent gates
Store the resolved mode for use in all subsequent phases.
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.mdEngine 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 casessubagent_type: gameplay-programmer— Implement the core gameplay codesubagent_type: ai-programmer— Implement NPC/enemy AI behaviorsubagent_type: technical-artist— Create VFX, shader effects, visual feedbacksubagent_type: sound-designer— Define audio events, impact sounds, ambient audiosubagent_type: [primary engine specialist]— Engine idiom validation for architecture and implementationsubagent_type: qa-tester— Write test cases and validate implementation
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 144 lines · 50 tokens per session scan A 8a3de29e9ac6
team-combat is a skill published in the GitHub repository Donchitos/Claude-Code-Game-Studios (24,822 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 1,688 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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Turn a novel into a fully playable game on the selected target platform. Orchestrates the whole adaptation pipeline — requirements intake, gameable deconstruction, concept selection, world and visual design, target-runtime build, and evidence-based QA — for a novel in any language. Use for novel to game, story to…
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game-world-design
Design game experience, systems, and levels. Converge the chosen concept into one GAMEDESIGN defining the player promise, core loop, how the world responds, the systems actually needed, level pacing, feedback, failure, and a fully playable prototype. Use for design the game world, deepen the gameplay and levels, write…
game-qa
Verify a game with evidence on its selected target runtime. Launch the actual build and prove real rendering, input, the core loop, at least one designed outcome, restart, and explicit limitations without dressing subjective fun up as a certain verdict. Use for test a generated game, QA a game build, check whether the…