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-levelnpx skills add Donchitos/Claude-Code-Game-Studios --skill team-levelgit 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-level)<a href="https://agentmods.dev/skills/donchitos/claude-code-game-studios/team-level"><img src="https://agentmods.dev/badge/skills/donchitos/claude-code-game-studios/team-level.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 5.1 | $0.00039 | $0.02477 |
| Opus 5 | $0.00019 | $0.01239 |
| Sonnet 5 | $0.00008 | $0.00495 |
| Haiku 4.5 | $0.00004 | $0.00248 |
Grade A, and why
team-level 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 2d ago.
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
4 near-identical copies found in the catalogue:
- team-level — 98% identical, 1 lines differ
- team-level — 91% identical, 23 lines differ
- team-level — 89% identical, 39 lines differ
- team-level — 86% identical, 46 lines differ
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When this skill is invoked:
Decision Points: At each step 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 step.
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.
-
Read the argument for the target level or area (e.g.,
tutorial,forest dungeon,hub town,final boss arena). -
Gather context:
- Read the game concept at
design/gdd/game-concept.md - Read game pillars at
design/gdd/game-pillars.md - Read existing level docs in
design/levels/ - Read relevant narrative docs in
design/narrative/ - Read world-building docs for the area's region/faction
- Read the game concept at
How to Delegate
Use the Task tool to spawn each team member as a subagent:
subagent_type: narrative-director— Narrative purpose, characters, emotional arcsubagent_type: world-builder— Lore context, environmental storytelling, world rulessubagent_type: level-designer— Spatial layout, pacing, encounters, navigationsubagent_type: systems-designer— Enemy compositions, loot tables, difficulty balancesubagent_type: art-director— Visual theme, color palette, lighting, asset requirementssubagent_type: accessibility-specialist— Navigation clarity, colorblind safety, cognitive loadsubagent_type: qa-tester— Test cases, boundary testing, playtest checklist
Always provide full context in each agent's prompt (game concept, pillars, existing level docs, narrative docs).
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.
- 2d ago First seen · 195 lines · 39 tokens per session scan A 2035d20d9393
team-level is a skill published in the GitHub repository Donchitos/Claude-Code-Game-Studios (24,822 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 2,477 once invoked, about $0.0002 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.
Other skills, from other repositories
novel-game-analyze
Deconstruct a novel for game adaptation. Compress a raw novel, deconstruction library, or writing project into a SOURCEBIBLE with cited textual evidence, extracting world rules, player verbs, spaces, character will, systems, and visual anchors — without inventing a genre yet. Use for gameable book analysis, analyze a…
novel-to-game
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…
game-build
Build a risk-matched whitebox or the approved production game for its target runtime. Turn GAMEDESIGN, and ARTDIRECTION when production begins, into a minimal BUILDBRIEF and a runnable candidate that can be iterated with replayable evidence. Use for prototype the riskiest design question, implement the approved game…
game-concept
Design game concepts from a novel. From SOURCEBIBLE and PRODUCTBRIEF, generate three genuinely different directions on the dimensions still unlocked, then pick the most worthwhile playable prototype using hard vetoes and explicit trade-offs. Use for what game should this novel become, compare game concepts, choose a…
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…