User asks for design, planning, or approach exploration before implementation. Covers new features, components, refactors, or architecture decisions. Creates design docs and proposes approaches with trade-offs.
中文简介正在准备中。当前显示原文说明。
Scan projects for credential leaks, secrets in code, insecure patterns, LLM API key exposure, PII leakage to external AI services, and .env/.gitignore misconfigurations. Especially useful for data and API integrations, regardless of implementation language.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Scan for credential leaks, insecure code patterns, and LLM security issues in Python data science projects.
.env, .gitignore, or config filesRead skills/scan-process.md for the full 6-step scan process with bash commands.
Read skills/pattern-tables.md for API key regex patterns, insecure Python code patterns, and LLM-specific security patterns with severity classifications.
Read guidelines.md for severity classifications, remediation requirements, and escalation rules.
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
User asks for design, planning, or approach exploration before implementation. Covers new features, components, refactors, or architecture decisions. Creates design docs and proposes approaches with trade-offs.
中文简介正在准备中。当前显示原文说明。
Use when starting work in a repository under repositories/ that may lack CI configuration. Detects missing CI workflows (GitHub Actions, GitLab CI, CircleCI) and alerts the user to add one. Skips repos marked as research-only.
中文简介正在准备中。当前显示原文说明。
Use when the user asks to measure command execution time or optimize a feedback loop. Records explicit measurements and recommends faster alternatives such as unit tests versus integration tests. It is opt-in; it does not run on every command.
中文简介正在准备中。当前显示原文说明。
Team conventions for Python development — credentials, API clients, LLM response parsing, testing patterns, and data pipeline structure. Covers dotenv loading, retry logic, secret validation, and pipeline anti-patterns.
中文简介正在准备中。当前显示原文说明。
Measurement-driven code refactoring — profile before changing, measure after, keep only if metrics improve. Covers complexity reduction, extraction patterns, and bulk refactoring for mechanical changes across many files.
中文简介正在准备中。当前显示原文说明。
Use when committing or pushing changes and the repository needs a version bump. Analyzes commits using conventional commit prefixes to determine whether the next release is a major, minor, or patch increment. Also use when the user asks about versioning, release planning, or changelog generation.
中文简介正在准备中。当前显示原文说明。