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 skills add IdoCohen560/claude-unity-game-studio --skill team-polishgit 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/skills/idocohen560/claude-unity-game-studio/team-polish)<a href="https://agentmods.dev/skills/idocohen560/claude-unity-game-studio/team-polish"><img src="https://agentmods.dev/badge/skills/idocohen560/claude-unity-game-studio/team-polish/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/skills/idocohen560/claude-unity-game-studio/team-polish"><img src="https://agentmods.dev/badge/skills/idocohen560/claude-unity-game-studio/team-polish.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 | $0.00045 | $0.01433 |
| Opus 5 | $0.00023 | $0.00717 |
| Sonnet 5 | $0.00009 | $0.00287 |
| Haiku 4.5 | $0.00005 | $0.00143 |
Grade A, and why
team-polish 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 7d 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
86% identical to team-polish — 18 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
If no argument is provided, output usage guidance and exit without spawning any agents:
Usage:
/team-polish [feature or area]— specify the feature or area to polish (e.g.,combat,main menu,inventory system,level-1). Do not useAskUserQuestionhere; output the guidance directly.
When this skill is invoked with an argument, orchestrate the polish 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
- performance-analyst — Profiling, optimization, memory analysis, frame budget
- engine-programmer — Engine-level bottlenecks: rendering pipeline, memory, resource loading (invoke when performance-analyst identifies low-level root causes)
- technical-artist — VFX polish, shader optimization, visual quality
- sound-designer — Audio polish, mixing, ambient layers, feedback sounds
- tools-programmer — Content pipeline tool verification, editor tool stability, automation fixes (invoke when content authoring tools are involved in the polished area)
- qa-tester — Edge case testing, regression testing, soak testing
How to Delegate
Use the Task tool to spawn each team member as a subagent:
subagent_type: performance-analyst— Profiling, optimization, memory analysissubagent_type: engine-programmer— Engine-level fixes for rendering, memory, resource loadingsubagent_type: technical-artist— VFX polish, shader optimization, visual qualitysubagent_type: sound-designer— Audio polish, mixing, ambient layerssubagent_type: tools-programmer— Content pipeline and editor tool verificationsubagent_type: qa-tester— Edge case testing, regression testing, soak testing
Always provide full context in each agent's prompt (target feature/area, performance budgets, known issues). Launch independent agents in parallel where the pipeline allows it (e.g., Phases 3 and 4 can run simultaneously).
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.
- 7d ago First seen · 125 lines · 45 tokens per session scan A e633feb53ee4
team-polish is a skill published in the GitHub repository IdoCohen560/claude-unity-game-studio (19 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 1,433 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to team-polish, differing in 18 lines, and is treated as a copy.
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test-writer
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abd-test
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plan-qa
Post-implementation QA planning — independent of /review (the developer chooses whether to run them sequentially or in parallel), only when the change has a running surface worth driving. Interviews the developer to turn the specs and the diff into an executable QA specification (specs/qa/QA- - .md) that /execute-qa…
execute-qa
Executes a QA specification (specs/qa/QA- - .md) written by /plan-qa: drives every step with the plan's drivers, verifies each Expected line mechanically ([assert]) or by evidence-backed judgment against the plan's written criterion ([judge]), pauses at named operator handoffs, and writes the results artifact…