Agent skill

Code Review Graph

by DanielSuo117 in DanielSuo117/velocitai

AST 知识图谱:变更审查、探索、调试、重构。触发:知识图谱、代码审查、影响分析、爆炸半径、重构. An agent skill from DanielSuo117/velocitai.

MITAuto-check passedDevelopment

Install Code Review Graph

skills CLI
$ npx skills add DanielSuo117/velocitai --skill code-review-graph -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install DanielSuo117/velocitai code-review-graph --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/DanielSuo117/velocitai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/code-review-graph .claude/skills/code-review-graph && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-review-graph
GitHub stars
158
Token cost
~460 tokens
SKILL.md length
154 words
Files
1
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

AST 知识图谱:变更审查、探索、调试、重构。触发:知识图谱、代码审查、影响分析、爆炸半径、重构. An agent skill from DanielSuo117/velocitai.

  • Works in 5 steps: 运行 detect_changes 获取带风险评分的变更分析。 → 运行 get_affected_flows 查找受影响的执行路径。 → 对高风险函数,运行 query_graph… → …
  • Tasks that involve Code review
  • SKILL.md covers Token 效率规则(全局), 工作流一:变更审查, 工作流二:代码库探索 and 工作流三:问题调试, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Review Graph is an agent skill from DanielSuo117/velocitai. AST 知识图谱:变更审查、探索、调试、重构。触发:知识图谱、代码审查、影响分析、爆炸半径、重构。

Its SKILL.md is about 460 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Code review. The repository describes itself as: Next-generation UI automation harness powered by Python & Playwright. Chat with AI Agents to seamlessly generate, architect, and execute enterprise-grade UI test code. The licence is MIT.

When your agent uses it

  • Tasks that involve Code review

Example prompts

  • “/code-review-graph”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. 运行 detect_changes 获取带风险评分的变更分析。
  2. 运行 get_affected_flows 查找受影响的执行路径。
  3. 对高风险函数,运行 query_graph pattern="tests_for" 检查测试覆盖。
  4. 运行 get_impact_radius 理解影响范围。
  5. 对未覆盖测试的变更,建议具体的测试用例。

What it can do on your machine

Read from SKILL.md and the folder at commit dfcca7e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code Review Graph loads about 460 tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 154 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~17
When it runs · the whole SKILL.md, loaded when a task matches
~460

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from DanielSuo117/velocitai at commit dfcca7e, republished under its MIT licence (© DanielSuo117). 154 words, ~460 tokens.

Download SKILL.mdSave it as .claude/skills/code-review-graph/SKILL.md (or your agent's skills folder).
name
code-review-graph
description
AST 知识图谱:变更审查、探索、调试、重构。触发:知识图谱、代码审查、影响分析、爆炸半径、重构。

code-review-graph — 知识图谱工具集

本项目通过 code-review-graph MCP 接入了基于 AST 的代码知识图谱。探索代码时优先使用图谱工具,再降级到 Grep/Glob/Read。

Token 效率规则(全局)

  • 始终先调用 get_minimal_context(task="<你的任务>"),再使用其他图谱工具。
  • 所有调用使用 detail_level="minimal",仅在不够用时升级到 "standard"。
  • 目标:5 次工具调用、800 个输出 token 内完成任务。

工作流一:变更审查

利用知识图谱进行风险感知的代码审查。

步骤
  1. 运行 detect_changes 获取带风险评分的变更分析。
  2. 运行 get_affected_flows 查找受影响的执行路径。
  3. 对高风险函数,运行 query_graph pattern="tests_for" 检查测试覆盖。
  4. 运行 get_impact_radius 理解影响范围。
  5. 对未覆盖测试的变更,建议具体的测试用例。
输出格式

按风险等级(高/中/低)分组,包含:变更内容、测试覆盖状态、改进建议、合并建议。


工作流二:代码库探索

利用图谱快速理解代码库结构。

步骤
  1. 运行 list_graph_stats 查看整体指标。
  2. 运行 get_architecture_overview 了解高层模块结构。
  3. 使用 list_communities 查找主要模块,用 get_community 获取详情。
  4. 使用 semantic_search_nodes 按名称或关键词查找函数/类。
  5. 使用 query_graph 的 callers_of、callees_of、imports_of 追踪关系。
  6. 使用 list_flows 和 get_flow 理解执行路径。
提示
  • 先宏观(统计、架构),再缩小到具体区域。
  • children_of 查看文件内所有函数和类;find_large_functions 定位复杂代码。

工作流三:问题调试

利用图谱系统化追踪和调试问题。

步骤
  1. 使用 semantic_search_nodes 查找与问题相关的代码。
  2. 使用 query_graph 的 callers_of 和 callees_of 追踪调用链。
  3. 使用 get_flow 查看可疑区域的完整执行路径。
  4. 运行 detect_changes 检查近期变更是否引发了问题。
  5. 对可疑文件使用 get_impact_radius 查看受影响范围。
提示
  • 同时检查调用者和被调用者,理解完整上下文。
  • 查看受影响的执行流,找到触发 bug 的入口点。
  • 近期变更是新问题最常见的来源。

工作流四:安全重构

利用图谱自信地规划和执行重构。

步骤
  1. 使用 refactor_tool mode="suggest" 获取重构建议。
  2. 使用 refactor_tool mode="dead_code" 查找死代码。
  3. 重命名时用 refactor_tool mode="rename" 预览所有受影响位置。
  4. 使用 apply_refactor_tool 配合 refactor_id 应用重命名。
  5. 变更后运行 detect_changes 验证影响。
安全检查
  • 应用前始终先预览(rename 模式给出编辑清单)。
  • 大规模重构前先检查 get_impact_radius。
  • 使用 get_affected_flows 确保关键路径未被破坏。
  • find_large_functions 识别需要拆分的大函数。

© DanielSuo117, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/code-review-graph of DanielSuo117/velocitai.

Open the folder on GitHubat commit dfcca7e

Compare with similar skills

Code Review Graph next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Code Review Graph compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Code Review Graph this skillDanielSuo117/velocitai158—~460Automated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
Backend Code Reviewlangflow-ai/langflow156k—~3.5kAutomated safety check: NotesMIT
Understand Diff AnalysisEgonex-AI/Understand-Anything85k1 repos~1.4kAutomated safety check: PassMIT
Mole Bug Patternstw93/Mole69k—~2kAutomated safety check: PassGPL-3.0

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Categories

Questions about Code Review Graph

What does Code Review Graph do?

AST 知识图谱:变更审查、探索、调试、重构。触发:知识图谱、代码审查、影响分析、爆炸半径、重构. An agent skill from DanielSuo117/velocitai. Code Review Graph is an agent skill from DanielSuo117/velocitai.

When should I use Code Review Graph?

Code Review Graph fits situations like: tasks that involve Code review.

How do I install Code Review Graph in Claude Code?

Run `npx skills add DanielSuo117/velocitai --skill code-review-graph -a claude-code`. Or copy the skill folder (skills/code-review-graph in DanielSuo117/velocitai) into .claude/skills/code-review-graph in your project. Claude Code loads it when a task matches its description.

How do I install Code Review Graph in Codex?

Run `npx skills add DanielSuo117/velocitai --skill code-review-graph -a codex`. Or copy the skill folder (skills/code-review-graph in DanielSuo117/velocitai) into .agents/skills/code-review-graph in your project. Codex loads it when a task matches its description.

Can I use Code Review Graph in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add DanielSuo117/velocitai --skill code-review-graph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review-graph, .gemini/skills/code-review-graph, .github/skills/code-review-graph and .opencode/skills/code-review-graph in your project.

What does Code Review Graph need to run?

SKILL.md names no scripts, command-line tools or credentials: Code Review Graph is instructions for the agent only.

Does Code Review Graph access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Code Review Graph safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Code Review Graph use?

Code Review Graph is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Review Graph use?

About 460 tokens (SKILL.md is roughly 1.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Review Graph?

Skills that share tags, products or a category with Code Review Graph: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Backend Code Review (langflow-ai/langflow, 156k stars) and Understand Diff Analysis (Egonex-AI/Understand-Anything, 85k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Review Graph?

DanielSuo117 (a GitHub user) maintains it in DanielSuo117/velocitai, which has 158 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on September 27, 2026.

Source: DanielSuo117/velocitai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.