local-ci-code-review 是什么？

适用场景： Ideal for AI agents that need local ci code review skill. 本地化技能摘要： Meta-skill for building AI-agnostic skill systems with a two-layer architecture of skills and roles, templates, validation tools, and cross-platform authoring guidance based on the Agent Skills specification. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

如何安装 local-ci-code-review？

运行命令：npx killer-skills add milanhorvatovic/skill-system-foundry/local-ci-code-review。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

local-ci-code-review 适用于哪些场景？

典型场景包括：适用任务： Applying Local CI Code Review Skill、适用任务： Applying Step 1: Identify the Changes、适用任务： Applying Determine the diff to review:。

local-ci-code-review 支持哪些 IDE 或 Agent？

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

local-ci-code-review 有哪些限制？

限制说明： Requires repository-specific context from the skill documentation；限制说明： Works best when the underlying tools and dependencies are already configured。

local-ci-code-review

安装 local-ci-code-review，这是一款面向AI agent workflows and automation的 AI Agent Skill。查看评审结论、使用场景与安装路径。

SKILL.md

Readonly

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Supporting Evidence

Local CI Code Review Skill

Name: local-ci-code-review
Availability: InStock
Author: milanhorvatovic

Runs a deep structured code review locally, applying the same methodology used by the codex-ai-code-review-action CI pipeline. Uses repository-specific guidance from .github/codex/review-reference.md and the review methodology defined below.

Step 1: Identify the Changes

Determine the diff to review:

bash
1# Changes on current branch vs main (default)
2git diff main...HEAD
3
4# Uncommitted changes (if no branch commits yet)
5git diff HEAD
6
7# Specific commit range (if provided)
8git diff <base>..<head>

If no scope is specified, default to main...HEAD.

List the changed files and note their types — file types determine which checklists apply in Step 3.

Step 2: Load Review Context

Read the repository-specific reference material and file-type instruction rules:

.github/codex/review-reference.md — repository-specific review guidance (conventions, Python script rules, workflow rules)
.github/copilot-instructions.md — Agent Skills format compliance, repository constraints, automated validation coverage, review focus areas
.github/instructions/markdown.instructions.md — documentation quality rules, description quality, progressive disclosure, file reference conventions
.github/instructions/scripts.instructions.md — Python script conventions, stdlib-only constraint, type hints, error handling, code organization rules

The review reference file provides repository-specific conventions — apply them alongside the methodology defined in this skill. The instruction files provide supplementary file-type-specific rules: apply copilot-instructions.md to all files, markdown.instructions.md when the diff includes **/*.md, and scripts.instructions.md when it includes skill-system-foundry/scripts/**/*.py.

Step 3: Review the Diff

Apply the review methodology from the loaded context. For each changed file:

Identify the file type and select the matching checklist from the reference material (Python, Shell, Markdown, Workflow YAML).
Trace data flow — follow values from input through parsing, transformation, and use.
Check execution order — verify validation happens before use.
Verify edge cases — empty arrays, zero, negatives, boundaries, missing optional fields.
Connect schema to runtime — check if documented contracts are enforced.
Check error propagation — verify callers handle failures.

For each finding, write the reasoning first, then assign priority and confidence.

Priority levels

Priority	Scope	Examples
P0	Critical bugs, security vulnerabilities	Data loss, injection, auth bypass, crash in mainline path
P1	Correctness and robustness	Off-by-one, unhandled error path, race condition
P2	Maintainability and style	Misleading name, duplicated logic, missing type hint
P3	Minor improvements	Whitespace, comment wording, optional simplification

Confidence scoring

Range	Meaning
0.9–1.0	Certain — code is demonstrably wrong or violates documented rule
0.7–0.9	High — very likely based on context, depends on intent
0.5–0.7	Moderate — plausible, could be intentional
0.3–0.5	Low — possible concern, may be false positive
< 0.3	Speculative — flag only if severe impact

Rules

Flag only issues introduced by the diff. Do not flag pre-existing problems.
Include findings at all priority levels — do not suppress low-priority findings.
Do not flag known limitations listed in the reference material.
Read the full source file when diff context is insufficient.

Step 4: Run the Self-Review Checklist

Before producing output, verify:

Every changed file in the diff has been examined.
The relevant file-type checklist was applied to each file.
Data flow was traced for any new parsing, transformation, or validation logic.
Edge cases were checked for new conditional branches or numeric conversions.
If zero findings, each file's clean status can be explained.

Step 5: Report Findings

Produce a structured review matching the CI pipeline output format.

Output format

## Summary
[1-5 sentence description of what the changes do and why]

## Changes
- [Short bullet describing each logical change]

## Files
| File | Description |
|---|---|
| path/to/file | Short description of what changed |

## Findings

### P0 — Critical
[findings or "None"]

### P1 — Correctness
[findings or "None"]

### P2 — Maintainability
[findings or "None"]

### P3 — Minor
[findings or "None"]

## Verdict
**[patch is correct | patch is incorrect]** (confidence: X.XX)
[One-sentence rationale]

Finding format

For each finding:

[P{n}] {title} — {path}:{line} (confidence: {score})

{body}
<details> <summary>Reasoning</summary> {reasoning — what was observed, why it is a problem, concrete impact} </details>
suggestion
1{exact replacement code, or omit block if null}

Metadata

After the verdict, append:

---
Findings: {total} ({skipped} below confidence threshold)
Model: {self-reported model identifier}
Review scope: {diff range used}

Rules

Empty findings is a valid outcome — a clean diff is not a failure to review.
Do not manufacture findings to justify the review.
Do not suggest alternative implementations unless the current one is clearly wrong.
Do not comment on style preferences without a documented convention backing them.

local-ci-code-review — for Claude Code local-ci-code-review, skill-system-foundry, community, for Claude Code, ide skills, codex-ai-code-review-action, copilot-instructions.md, markdown.instructions.md, scripts.instructions.md, reasoning

关于此技能

功能特性

# 核心主题

Killer-Skills Review

核心价值

适用 Agent 类型

↓ 赋予的主要能力 · local-ci-code-review

! 使用限制与门槛

Why this page is reference-only

Source Boundary

先决定动作，再继续看上游仓库材料

先进入安装与验证

回到可信合集再做一次复核

如果要进团队流转，转到工作流集合

Browser Sandbox Environment

⚡️ Ready to unleash?

常见问题与安装步骤

? FAQ

local-ci-code-review 是什么？

如何安装 local-ci-code-review？

local-ci-code-review 适用于哪些场景？

local-ci-code-review 支持哪些 IDE 或 Agent？

local-ci-code-review 有哪些限制？

↓ 安装步骤

! 参考页模式

Upstream Repository Material

local-ci-code-review

Local CI Code Review Skill

Step 1: Identify the Changes

Step 2: Load Review Context

Step 3: Review the Diff

Priority levels

Confidence scoring

Rules

Step 4: Run the Self-Review Checklist

Step 5: Report Findings

Output format

Finding format

Metadata

Rules

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