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 u9401066/template-is-all-you-need --skill code-reviewergit clone --depth 1 https://github.com/u9401066/template-is-all-you-needWrote 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/u9401066/template-is-all-you-need/code-reviewer)<a href="https://agentmods.dev/skills/u9401066/template-is-all-you-need/code-reviewer"><img src="https://agentmods.dev/badge/skills/u9401066/template-is-all-you-need/code-reviewer/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/u9401066/template-is-all-you-need/code-reviewer"><img src="https://agentmods.dev/badge/skills/u9401066/template-is-all-you-need/code-reviewer.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 | $0.00089 | $0.01710 |
| Opus 5 | $0.00044 | $0.00855 |
| Sonnet 5 | $0.00018 | $0.00342 |
| Haiku 4.5 | $0.00009 | $0.00171 |
Grade A, and why
code-reviewer 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-reviewer — 100% identical, 0 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.
程式碼審查技能
描述
對程式碼進行全面審查，檢查品質、安全性、效能和最佳實踐。
觸發條件
- 「review 這段程式碼」「CR」「審查」
- 「檢查程式碼」「看一下」「幫看」
- 「code review」「PR review」
🔧 操作步驟
Step 1: 確定審查範圍
詢問或推斷審查目標：
- 特定檔案：
read_file("path/to/file.py") - 整個目錄：
grep_search取得概覽 - 特定功能：
semantic_search("功能名稱") - 最近變更：
get_changed_files()
Step 2: 執行靜態分析（Python 專案）
# Ruff - 快速 linter (取代 flake8 + isort + pyupgrade)
uv run ruff check src/ --output-format=concise
# Mypy - 型別檢查
uv run mypy src/ --ignore-missing-imports
# Bandit - 安全性檢查
uv run bandit -r src/ -ll
# Vulture - 死碼偵測
uv run vulture src/ --min-confidence 80
Step 3: 審查程式碼品質
| 檢查項目 | 標準 | 工具輔助 |
|---|---|---|
| 命名清晰度 | 名稱應描述用途 | 人工審查 |
| 函數長度 | < 50 行 | grep_search |
| 類別大小 | < 300 行 | grep_search |
| 複雜度 | McCabe < 10 | ruff --select=C901 |
| DRY 原則 | 無重複程式碼 | semantic_search |
| SOLID 原則 | 單一職責等 | 人工審查 |
Step 4: 審查安全性
| 風險類型 | 檢查方式 | 嚴重程度 |
|---|---|---|
| SQL 注入 | 搜尋 raw SQL | 🔴 Critical |
| XSS | 搜尋未轉義輸出 | 🔴 Critical |
| 硬編碼密碼 | grep "password|secret|key" | 🔴 Critical |
| 路徑遍歷 | 搜尋未驗證路徑 | 🟠 High |
| 日誌洩漏 | 搜尋敏感資料輸出 | 🟡 Medium |
Step 5: 審查效能
| 問題類型 | 偵測方式 |
|---|---|
| N+1 查詢 | 搜尋迴圈內的 DB 呼叫 |
| 無謂迴圈 | 審查巢狀迴圈 |
| 記憶體洩漏 | 檢查資源釋放 |
| 阻塞操作 | 審查 I/O 操作 |
Step 6: 審查 DDD 架構
參考 ddd-architect 規則：
- Domain 層是否有外部依賴？
- Repository Interface 是否在 Domain 層？
- Application 層是否過度膨脹？
Step 7: 產生審查報告
📊 審查報告格式
# 程式碼審查報告
📁 審查範圍：`src/domain/`, `src/application/`
📅 日期：2026-01-15
👤 審查者：AI Assistant
---
## 📈 總覽
| 指標 | 分數 | 說明 |
| ---- | ---- | ---- |
| 品質 | 8/10 | 命名清晰，部分函數過長 |
| 安全 | 9/10 | 無明顯漏洞 |
| 效能 | 7/10 | 存在 N+1 查詢風險 |
| 架構 | 8/10 | 符合 DDD，但有小違規 |
---
## ✅ 優點
1. **清晰的領域模型**：User entity 封裝良好
2. **完整的錯誤處理**：使用自定義例外
3. **良好的測試覆蓋**：核心邏輯有單元測試
---
## ⚠️ 問題發現
### 🔴 Critical (必須修復)
#### 1. SQL 注入風險
- **位置**：[user_repository.py](src/infrastructure/repositories/user_repository.py#L45)
- **問題**：使用字串拼接建立 SQL
- **建議**：使用參數化查詢
```python
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 · 195 lines · 0 tokens per session scan A c828461b4e15
code-reviewer is a skill published in the GitHub repository u9401066/template-is-all-you-need (3 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 89 tokens to every session and 1,710 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
code-review-architecture
Architecture-focused code review covering hexagonal boundary violations, DDD anti-patterns, CQRS misuse, and microservices coupling issues. Applied in addition to the language-specific review skill when architecture markers are detected. Invoked when reviewing hexagonal architectures, DDD patterns, or microservices…
Code Review Checklist
Runs a systematic checklist review on any code diff or file, covering correctness, security, performance, and readability.
ledger-audit
Retrospective pass over a project built before the ledger existed: reconstruct the structural decisions already made and the conventions applied without a reason. (decision-ledger).
ledger-report
Mastery map for this project: which areas of the codebase are defended, which are thin. Run it at a commit, a pull request, or on request. (decision-ledger).
clean-code-reviewer
Reviews code against Robert C. Martin's Clean Code principles. Use when users share code for review, ask for refactoring suggestions, or want to improve code quality. Produces actionable feedback organized by Clean Code principles with concrete before/after examples.
code-review
Reviews code changes using CodeRabbit AI. Use when user asks for code review, PR feedback, code quality checks, security issues, or wants autonomous fix-review cycles.