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 architecture-reviewgit 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/architecture-review)<a href="https://agentmods.dev/skills/idocohen560/claude-unity-game-studio/architecture-review"><img src="https://agentmods.dev/badge/skills/idocohen560/claude-unity-game-studio/architecture-review/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/architecture-review"><img src="https://agentmods.dev/badge/skills/idocohen560/claude-unity-game-studio/architecture-review.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 | $0.00071 | $0.05924 |
| Opus 5 | $0.00036 | $0.02962 |
| Sonnet 5 | $0.00014 | $0.01185 |
| Haiku 4.5 | $0.00007 | $0.00592 |
Grade A, and why
architecture-review 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 12d 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 architecture-review — 60 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 — 640 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Review
The architecture review validates that the complete body of architectural decisions covers all game design requirements, is internally consistent, and correctly targets the project's pinned engine version. It is the quality gate between Technical Setup and Pre-Production.
Argument modes:
- No argument /
full: Full review — all phases coverage: Traceability only — which GDD requirements have no ADRconsistency: Cross-ADR conflict detection onlyengine: Engine compatibility audit onlysingle-gdd [path]: Review architecture coverage for one specific GDDrtm: Requirements Traceability Matrix — extends the standard matrix to include story file paths and test file paths; outputsdocs/architecture/requirements-traceability.mdwith the full GDD requirement → ADR → Story → Test chain. Use in Production phase when stories and tests exist.
Phase 1: Load Everything
Phase 1a — L0: Summary Scan (fast, low tokens)
Before reading any full document, use Grep to extract ## Summary sections
from all GDDs and ADRs:
Grep pattern="## Summary" glob="design/gdd/*.md" output_mode="content" -A 4
Grep pattern="## Summary" glob="docs/architecture/adr-*.md" output_mode="content" -A 3
For single-gdd [path] mode: use the target GDD's summary to identify which
ADRs reference the same system (Grep ADRs for the system name), then full-read
only those ADRs. Skip full-reading unrelated GDDs entirely.
For engine mode: only full-read ADRs — GDDs are not needed for engine checks.
For coverage or full mode: proceed to full-read everything below.
Phase 1b — L1/L2: Full Document Load
Read all inputs appropriate to the mode:
Design Documents
- All in-scope GDDs in
design/gdd/— read every file completely design/gdd/systems-index.md— the authoritative list of systems
Architecture Documents
- All in-scope ADRs in
docs/architecture/— read every file completely docs/architecture/architecture.mdif it exists
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.
- 12d ago First seen · 640 lines · 71 tokens per session scan A b5980b7d91bf
architecture-review is a skill published in the GitHub repository IdoCohen560/claude-unity-game-studio (19 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 5,924 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to architecture-review, differing in 60 lines, and is treated as a copy.
Other skills, from other repositories
swarm
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architecture-review
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code-review
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abd-review
ABD Tech Review agent: reviews code quality, architecture, naming, and error handling; writes severity-graded review artifacts.
review
Phase 5 of 5 — triage-first review orchestrator; dispatches up to 17 domain checks in parallel and compiles one report. Use only when the user asks to run Phase 5 or review a PR, branch, or set of changes — never trigger automatically after writing code.
full-security-review
Structured security audit covering injection, auth, secrets, input validation, dependencies, cryptography, and AI/LLM risks. Produces severity-graded findings.