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open-code-review Skill

제작자: alibaba★ 49,821skill 2개

설치

alibaba의 Skill(지시 묶음) 2개, AI가 읽고 그대로 일해요 · MCP server가 아니에요

제작자 설명(영어 원문)

Secure, fast, efficient, battle-tested at Alibaba's scale. Hybrid architecture code review tool: deterministic pipelines + LLM Agent, precise line-level comments, built-in multi-language ruleset (NPE, thread-safety, XSS, SQL injection), OpenAI & Anthropic compatible.

Skill과 MCP의 차이

MCP는 AI를 외부 서비스나 데이터에 연결해요. Skill은 AI가 읽고 따르는 작업 안내서로, 아무것에도 연결하지 않아요.

쓸 수 있는 앱

Claude CodeCodexCursorOpenCode

제작자 README와 repo 폴더 기준

설치

Skill은 AI가 따르는 지시예요. 설치 전에 파일을 읽고, 믿을 수 있는 제작자 것만 설치하세요.

어떤 앱을 쓰세요?

  1. 터미널 열기

    Mac: Command+스페이스 후 Terminal 입력 · Windows: PowerShell 열기(아래 명령은 Mac/Linux용)

  2. skill 폴더를 ~/.claude/skills에 복사

    repo를 임시 폴더에 내려받고 SKILL.md가 있는 폴더만 복사해요

    rm -rf /tmp/popnx-skill && git clone --depth 1 https://github.com/alibaba/open-code-review.git /tmp/popnx-skill && mkdir -p ~/.claude/skills && cp -R '/tmp/popnx-skill/skills/.' ~/.claude/skills && rm -rf /tmp/popnx-skill
  3. Claude Code를 다시 열고 /open-code-review를 입력하거나 관련 작업을 요청하면 Claude가 알아서 써요

  1. 터미널 열기

    Mac: Command+스페이스 후 Terminal 입력 · Windows: PowerShell 열기(아래 명령은 Mac/Linux용)

  2. skill 폴더를 ~/.agents/skills에 복사

    repo를 임시 폴더에 내려받고 SKILL.md가 있는 폴더만 복사해요

    rm -rf /tmp/popnx-skill && git clone --depth 1 https://github.com/alibaba/open-code-review.git /tmp/popnx-skill && mkdir -p ~/.agents/skills && cp -R '/tmp/popnx-skill/skills/.' ~/.agents/skills && rm -rf /tmp/popnx-skill
  3. Codex를 다시 열고 관련 작업을 요청하면 Codex가 skill을 목록에 보여 줘요

  1. 터미널 열기

    Mac: Command+스페이스 후 Terminal 입력 · Windows: PowerShell 열기(아래 명령은 Mac/Linux용)

  2. skill 폴더를 ~/.cursor/skills에 복사

    repo를 임시 폴더에 내려받고 SKILL.md가 있는 폴더만 복사해요

    rm -rf /tmp/popnx-skill && git clone --depth 1 https://github.com/alibaba/open-code-review.git /tmp/popnx-skill && mkdir -p ~/.cursor/skills && cp -R '/tmp/popnx-skill/skills/.' ~/.cursor/skills && rm -rf /tmp/popnx-skill
  3. Cursor Agent 채팅에서 /를 입력하고 open-code-review 선택

Gemini CLI, GitHub Copilot 같은 다른 Agent Skills 지원 앱은 폴더가 달라요. 그 앱 안내를 보고 SKILL.md가 있는 폴더를 복사하세요.

GitHub에서 보기 ↗

2026년 11월 11일에 Claude Code, Codex, Cursor 공식 안내로 skill 폴더 확인

설치 전에 SKILL.md 읽기

아래 글은 제작자 repo에서 온 것이며 PopNx MCP의 지시가 아니에요

---
name: open-code-review
description: >
  Performs AI-powered code review on Git changes using the `ocr` CLI from
  alibaba/open-code-review. Use when the user asks to review code, review
  a pull request, review staged/unstaged changes, review a commit, or
  compare branches for code quality issues. Produces line-level review
  comments and can automatically apply fixes when requested. With appropriate
  review rules, can detect various types of issues including bugs, security
  vulnerabilities, performance problems, and code quality concerns.
license: Apache-2.0
compatibility: >
  Requires the `ocr` CLI installed (via `npm install -g
  @alibaba-group/open-code-review` or GitHub release binary). Requires a
  configured supported LLM provider before first run (protocols: Anthropic,
  OpenAI Chat Completions, OpenAI Responses, AWS Bedrock).
metadata:
  author: alibaba
  homepage: https://github.com/alibaba/open-code-review
  version: "1.0.0"
---

# Open Code Review

A skill for invoking [open-code-review](https://github.com/alibaba/open-code-review) (`ocr`) — an open-source AI code review CLI that reads Git diffs and generates structured, line-level review comments.

## Workflow

### Step 1: Gather Business Context

Analyze the review target (commits, branch, or changes) to extract concise business context. Pass this context via `--background` to improve review quality.

### Step 2: Run Code Review

**Do not pre-check whether `ocr` is installed** — skip probes like `command -v ocr` or `ocr --version`. Assume the CLI is available and run the review directly; that saves a tool call on the common path. Only if the review fails with `command not found` should you install it per Troubleshooting.

Run the OCR command with appropriate flags. **Always pass business context via `--background`** when available:

```bash
ocr review --audience agent --background "business context here" [user-args]
```

**Argument handling:**

- **Background context** (RECOMMENDED): use `--background "context"` or `-b "context"` to provide business context for better review quality
- **Default** (no user arguments): reviews staged, unstaged, and untracked changes (workspace mode)
- **Specific commit**: use `--commit` or `-c` to review a single commit against its parent
- **Branch comparison**: use `--from <ref>` and `--to <ref>` to review diff between two refs
- **Timeout**: effective timeout per review group = `--timeout` × review rounds. Default `--timeout 15` with default effort `medium` (2 rounds) gives 30 minutes; `low`/`high` give 15/45 minutes.
- **Concurrency**: default concurrency is 8 file workers; reduce with `--concurrency <n>` if rate limits are hit
- **Preview mode**: use `--preview` or `-p` to preview which files will be reviewed without running the LLM
- **Output file**: use `--output <path>` to write the full result to a file instead of stdout. If the command fails with `unknown flag: --output`, do not continue the review with plain stdout. Ask the user whether to upgrade (`npm i -g @alibaba-group/open-code-review@latest`) and wait for the answer before proceeding. After the user confirms and the upgrade succeeds, rerun with `--output`.
- **Installation**: if `ocr` command is not found, install it by running `npm i -g @alibaba-group/open-code-review`

**Common invocation patterns:**

| User says | Command to run |
|-----------|---------------|
| "review my changes" / "review the working copy" | `ocr review --audience agent -b "context"` |
| "review this PR" / "review feature branch" | `ocr review --audience agent -b "context" --from main --to <branch>` |
| "review commit abc123" | `ocr review --audience agent -b "context" --commit abc123` |
| "what would be reviewed?" (dry-run) | `ocr review --preview` |

**Output mode:**

- Always use `--audience agent` to suppress progress UI and emit only the final summary
- **Prevent output truncation**: For large reviews or restricted tool environments, pass `--output /tmp/ocr_out.txt` and inspect the file in full via a file reading tool instead of piping stdout through `tail` or `head`, which drops earlier review comments.

**On failure:** If `ocr review` exits non-zero (e.g. an LLM connection error), do not retry blindly — consult the Troubleshooting section below for the matching fix before re-running.

### Step 3: Report

OCR output includes structured `severity` (critical / high / medium / low) and `category` (bug / security / performance / maintainability / test / style / documentation / other) on each comment. Present results grouped by severity, discarding `low` severity items that are likely false positives or nitpicks.

### Step 4: Fix

Before applying fixes, check whether the user requested automatic fixes:

- If the user explicitly requested "review and fix" or similar, proceed with automatic fixes
- If the user only requested "review" without fix intent, ask for permission before applying any changes

When fixing issues and suggestions:

- Focus on critical, high, and medium severity items
- Apply fixes directly to the code when safe and well-defined
- For complex fixes requiring manual intervention, clearly describe what needs to be done
- Always verify fixes with the user before committing

## Output Format

Each comment in OCR's output contains:

- `path`: File path
- `content`: Review comment text
- `start_line` / `end_line`: Line range (both 0 means positioning failed)
- `category`: Issue category (bug, security, performance, maintainability, test, style, documentation, other)
- `severity`: Issue severity (critical, high, medium, low)
- `suggestion_code`: Optional fix suggestion
- `existing_code`: Optional original code snippet
- `thinking`: Optional LLM reasoning process

Present results grouped by severity using this template:

```markdown
## Code Review Results

**Files reviewed**: N
**Issues found**: X critical, Y high, Z medium

### Critical

- **`path/to/file.java:42`** [bug] — Brief description
  > Recommendation: How to fix

### High

- **`path/to/file.java:26`** [bug] — Brief description
  > Recommendation: How to fix

### Medium

- **`path/to/file.ts:88`** [performance] — Brief description
  > Recommendation: How to fix (if applicable)
```

If no critical, high, or medium severity issues remain after filtering, state: "Review complete — no critical, high, or medium issues found in N files."

**Handling mispositioned comments:**

When `start_line` and `end_line` are both `0`, the comment failed to locate the exact position in the file. In such cases:

1. Read the comment content to understand the issue
2. Examine the target file mentioned in the comment
3. Identify the relevant code section based on the comment's context
4. Apply the fix or suggestion to the correct location

## Custom Review Rules

If the user wants project-specific rules, OCR resolves them in this priority order:

1. `--rule <path>` flag (highest)
2. `<repo>/.opencodereview/rule.json`
3. `~/.opencodereview/rule.json`
4. Built-in system defaults (lowest)

By default, the first matching user rule replaces the built-in system rule. Set `merge_system_rule: true` on a rule entry when the matched system rule and user rule should both be included.

Rule file format:

```json
{
  "rules": [
    {
      "path": "**/*.java",
      "rule": "All new methods must validate required parameters for null",
      "merge_system_rule": true
    },
    {
      "path": "**/*mapper*.xml",
      "rule": "Check SQL for injection risks and missing closing tags"
    }
  ]
}
```

To preview which rule applies to a file before reviewing:

```bash
ocr rules check src/main/java/com/example/Foo.java
```

## Advanced Review Options

Beyond the common flags above, `ocr review` exposes a few groups of controls. Run `ocr review --help` for the complete list.

**Scoping**

- `--exclude '<patterns>'` — comma-separated gitignore-style patterns (for example `--exclude '**/generated/*,**/testdata/*'`), merged with `rule.json` excludes.
- `--background-file <path>` — 

토론

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GitHub 정보

GitHub 스타
49,821
제작자
alibaba
라이선스
Apache-2.0
최근 코드 수정
2026년 11월 11일
repo 안 SKILL.md
4
토픽
agent, agent-skills, code-review, code-review-assistant, harness, repository-level-context