ワンクリックで
ワンクリックで
| name | code-review |
| description | 进行全面代码审查,覆盖安全、正确性、性能与可维护性;适用于用户要求 review、排查潜在 bug 或审计代码库。 |
You now have expertise in conducting comprehensive code reviews. Follow this structured approach:
Check for:
npm audit, pip-audit)# Quick security scans
npm audit # Node.js
pip-audit # Python
cargo audit # Rust
grep -r "password\|secret\|api_key" --include="*.py" --include="*.js"
Check for:
Check for:
Check for:
Check for:
## Code Review: [file/component name]
### Summary
[1-2 sentence overview]
### Critical Issues
1. **[Issue]** (line X): [Description]
- Impact: [What could go wrong]
- Fix: [Suggested solution]
### Improvements
1. **[Suggestion]** (line X): [Description]
### Positive Notes
- [What was done well]
### Verdict
[ ] Ready to merge
[ ] Needs minor changes
[ ] Needs major revision
# Bad: SQL injection
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")
# Good:
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
# Bad: Command injection
os.system(f"ls {user_input}")
# Good:
subprocess.run(["ls", user_input], check=True)
# Bad: Mutable default argument
def append(item, lst=[]): # Bug: shared mutable default
# Good:
def append(item, lst=None):
lst = lst or []
// Bad: Prototype pollution
Object.assign(target, userInput)
// Good:
Object.assign(target, sanitize(userInput))
// Bad: eval usage
eval(userCode)
// Good: Never use eval with user input
// Bad: Callback hell
getData(x => process(x, y => save(y, z => done(z))))
// Good:
const data = await getData();
const processed = await process(data);
await save(processed);
# Show recent changes
git diff HEAD~5 --stat
git log --oneline -10
# Find potential issues
grep -rn "TODO\|FIXME\|HACK\|XXX" .
grep -rn "password\|secret\|token" . --include="*.py"
# Check complexity (Python)
pip install radon && radon cc . -a
# Check dependencies
npm outdated # Node
pip list --outdated # Python
商业级视觉资产与网页(详情页/落地页)的审美与UX视觉审查:输出P0/P1/P2问题清单、可落地的样式tokens与改稿建议;可结合截图、URL与源码进行定位与修改。
设计并构建各类 AI 智能体/助手。适用于用户: (1) 询问“创建 agent / 助手 / 智能体系统” (2) 想理解 agent 架构、agentic 模式或自治式 AI (3) 需要能力设计、子代理、规划或 skills 机制建议 (4) 询问 Claude Code、Cursor 等智能体内部实现 (5) 想为业务/研究/创作/运营等场景构建 agent 关键词:agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
启用 agents-team 协作,双代理完成小说逐章元数据抽取与完整性审校(parser + checker),并写入可续跑的记忆索引。
Enable general multi-agent team mode via spawn_agent/wait tools. Supports orchestrator, worker, reviewer, research, writer, and editor roles.
Agents-CLI 认知记忆系统。用于管理长期记忆(core/episodic/semantic/procedural/vault)、可检索回忆、归档遗忘、以及多代理写入治理。
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.