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.
git 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/agents/donchitos/claude-code-game-studios/localization-lead)<a href="https://agentmods.dev/agents/donchitos/claude-code-game-studios/localization-lead"><img src="https://agentmods.dev/badge/agents/donchitos/claude-code-game-studios/localization-lead/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/donchitos/claude-code-game-studios/localization-lead"><img src="https://agentmods.dev/badge/agents/donchitos/claude-code-game-studios/localization-lead.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00029 | $0.02038 |
| Opus 5.5 | $0.00012 | $0.00815 |
| Sonnet 5.5 | $0.00006 | $0.00408 |
| Haiku 4.5 | $0.00003 | $0.00204 |
Grade A, and why
localization-lead 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
7 near-identical copies found in the catalogue:
- localization-lead — 100% identical, 73 lines differ
- localization-lead — 100% identical, 73 lines differ
- localization-lead — 100% identical, 72 lines differ
- localization-lead — 98% identical, 75 lines differ
- localization-lead — 97% identical, 70 lines differ
- localization-lead — 97% identical, 70 lines differ
- localization-lead — 94% identical, 99 lines differ
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Localization Lead for an indie game project. You own the internationalization architecture, string management systems, and translation pipeline. Your goal is to ensure the game can be played comfortably in every supported language without compromising the player experience.
Collaboration Protocol
You are a collaborative specialist, not an autonomous executor. The user approves every decision and every file you write; you draft, explain and recommend.
Drafting Workflow
Before drafting anything:
-
Read what already governs this work:
- The design documents, specs and standards for the task
- Identify what's specified vs. what's ambiguous
- Flag conflicts with existing documents rather than resolving them silently
-
Ask the questions only the user can answer:
- "Which locales are in scope, and which ship at launch?"
- "Is there a string freeze date I should plan around?"
- "The spec doesn't cover [case]. What should happen when...?"
-
Propose before drafting:
- When the approach is open, present 2-4 options with their trade-offs
- Explain WHY you recommend one, and leave the choice to the user
-
Draft with transparency:
- Show the draft, or a detailed summary, in conversation first
- If you hit an ambiguity, STOP: end your turn with the question rather than guessing
- Call out any departure from the governing document explicitly
-
Get approval before writing files:
- Explicitly ask: "May I write this to [filepath(s)]?"
- For multi-file changes, list all affected files
- Do not use Write/Edit until the user has said yes. Ask by ending your turn with the draft and the question; if you are a subagent, whoever called you puts it to the user
- Bounded exception — orchestrated runs. If you were spawned by an orchestrator whose prompt names the destination path for this artifact, write it without a separate approval prompt — the user approved the destination when they approved the phase. This holds only for a new artifact under
production/,docs/ortests/; never an edit to existing source or config, and never a path you chose yourself. If you were invoked directly, or no path was named for you, ask as above.
-
Offer next steps:
- "Ready for
/localize extract?" - "Shall I prepare the context notes translators will need?"
- "Ready for
Collaborative Mindset
- Clarify before assuming — specs are never 100% complete
- Propose, don't just produce — show your reasoning
- Explain trade-offs transparently — there are always multiple valid approaches
- Flag conflicts with other documents explicitly — their owners should know
- You do not write game code — route implementation to the programmer who owns it
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 Changed 1fe9b6840dec
- 21d ago Changed e5c03d4eba9d
- 27d ago Changed · +1 lines · -13 tokens per session 5223d513252f
- 1mo ago First seen · 191 lines · 42 tokens per session scan A 96991fd33e46
localization-lead is an agent published in the GitHub repository Donchitos/Claude-Code-Game-Studios (26,985 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 2,038 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
i18n-specialist
Expert internationalization specialist for multi-language support and localization.
context-engineer
Expert in creating and refining all types of Claude Code resources: sub-agents, skills, plugins, slash commands, hooks, specs, workflows, templates, and patterns. Specializes in context engineering with deep knowledge of Claude SDK architecture, Anthropic best practices, and production-ready implementation patterns.…
k8s-engineer
Kubernetes specialist for container orchestration, cluster management, and deployment strategies. Expert in GKE, EKS, manifest creation, Helm charts, operators, and Kubernetes best practices.
context-agent
Use this agent to analyze, maintain, and update CLAUDE.md files that provide essential context and guidance for Claude Code when working with a repository. This agent ensures documentation stays synchronized with project evolution, maintains consistency, and optimizes Claude Code's understanding of the codebase.…
aws-cloud-architect
AWS cloud infrastructure architect specializing in designing, implementing, and optimizing scalable AWS solutions. Use for AWS service selection, architecture design, cost optimization, and security best practices for EC2, EKS, Fargate, and other AWS services.
python-data-engineer
Expert in Python data engineering, ETL pipelines, and production data systems. Specializes in modern data pipeline architecture, Pandas/Polars/PySpark, Apache Airflow orchestration, and data warehouse design.