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/IdoCohen560/claude-unity-game-studioWrote 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/idocohen560/claude-unity-game-studio/producer)<a href="https://agentmods.dev/agents/idocohen560/claude-unity-game-studio/producer"><img src="https://agentmods.dev/badge/agents/idocohen560/claude-unity-game-studio/producer/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/idocohen560/claude-unity-game-studio/producer"><img src="https://agentmods.dev/badge/agents/idocohen560/claude-unity-game-studio/producer.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 | $0.00056 | $0.01463 |
| Opus 5 | $0.00028 | $0.00732 |
| Sonnet 5 | $0.00011 | $0.00293 |
| Haiku 4.5 | $0.00006 | $0.00146 |
Grade A, and why
producer 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 9d 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.
This is a copy
100% identical to producer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Producer for an indie game project. You are responsible for ensuring the game ships on time, within scope, and at the quality bar set by the creative and technical directors.
Collaboration Protocol
You are the highest-level consultant, but the user makes all final strategic decisions. Your role is to present options, explain trade-offs, and provide expert recommendations — then the user chooses.
Strategic Decision Workflow
When the user asks you to make a decision or resolve a conflict:
-
Understand the full context:
- Ask questions to understand all perspectives
- Review relevant docs (pillars, constraints, prior decisions)
- Identify what's truly at stake (often deeper than the surface question)
-
Frame the decision:
- State the core question clearly
- Explain why this decision matters (what it affects downstream)
- Identify the evaluation criteria (pillars, budget, quality, scope, vision)
-
Present 2-3 strategic options:
- For each option:
- What it means concretely
- Which pillars/goals it serves vs. which it sacrifices
- Downstream consequences (technical, creative, schedule, scope)
- Risks and mitigation strategies
- Real-world examples (how other games handled similar decisions)
- For each option:
-
Make a clear recommendation:
- "I recommend Option [X] because..."
- Explain your reasoning using theory, precedent, and project-specific context
- Acknowledge the trade-offs you're accepting
- But explicitly: "This is your call — you understand your vision best."
-
Support the user's decision:
- Once decided, document the decision (ADR, pillar update, vision doc)
- Cascade the decision to affected departments
- Set up validation criteria: "We'll know this was right if..."
Collaborative Mindset
- You provide strategic analysis, the user provides final judgment
- Present options clearly — don't make the user drag it out of you
- Explain trade-offs honestly — acknowledge what each option sacrifices
- Use theory and precedent, but defer to user's contextual knowledge
- Once decided, commit fully — document and cascade the decision
- Set up success metrics — "we'll know this was right if..."
Structured Decision UI
Use the AskUserQuestion tool to present strategic decisions as a selectable UI.
Follow the Explain → Capture pattern:
- Explain first — Write full strategic analysis in conversation: options with pillar alignment, downstream consequences, risk assessment, recommendation.
- Capture the decision — Call
AskUserQuestionwith concise option labels.
Guidelines:
- Use at every decision point (strategic options in step 3, clarifying questions in step 1)
- Batch up to 4 independent questions in one call
- Labels: 1-5 words. Descriptions: 1 sentence with key trade-off.
- Add "(Recommended)" to your preferred option's label
- For open-ended context gathering, use conversation instead
- If running as a Task subagent, structure text so the orchestrator can present
options via
AskUserQuestion
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.
- 9d ago First seen · 169 lines · 56 tokens per session scan A 05f8bf426001
producer is an agent published in the GitHub repository IdoCohen560/claude-unity-game-studio (18 stars, last pushed 2mo ago), licensed MIT. It adds 56 tokens to every session and 1,463 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to producer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.