cloudbase-ai-toolkit

Use when auditing CloudBase cloud API wrappers, MCP tools, generated action metadata, or related docs for outdated or incorrect action names, parameters, casing, request shapes, or missing contract tests, especially during periodic quality review or before preparing corrective PRs.

Author or revise a cloud-api-operations recipe (config/source/skills/cloud-api-operations/references/recipes/). Encodes why the long tail of control-plane capabilities is deliberately NOT wrapped as MCP/CLI tools, the API-first admission test for whether a capability deserves a recipe, the negative and positive lists, the fixed recipe structure, the writing rules distilled from writing-for-agents, the user-facing copy red lines, and the product regeneration/verification pipeline. Also routes contributors (and their agents) to the contribution flow and the pre-PR self-test protocol in references/contributing.md. Use when adding a recipe, judging whether a scenario belongs in the recipe set, updating the recipes index, re-checking existing recipes against the admission test, or onboarding someone who wants to submit one.

Perform a full codebase review, categorize findings by severity, file GitHub issues, then fix each issue in an isolated git worktree and submit PRs. Use this skill when the user asks to audit the codebase, do a comprehensive code review, find and fix security/quality/reliability issues, or run a proactive health check across the entire repository.

升级 CodeBuddy IDE（genie 扩展）内置的 CloudBase MCP，以及 MCP 发版时同步 IDE 侧白名单。当用户提到「更新 IDE 里的 MCP」「内置 MCP 版本太老」「IDE 集成的 CloudBase 功能不足」「改工具白名单 toolWhiteList」「把新 bundle 打进 CodeBuddy」「白名单漂移」「MCP 发版要同步什么」时使用。覆盖：解包定位内置 bundle 与内嵌配置、重新构建 mcp bundle、生成新的工具白名单与系统提示词、安全注入 IDE 并备份、用 MCP 协议验证工具清单、人工端到端验收、一键回滚。

Use when auditing repository documentation for drift, stale statements, broken references, or README mismatches, especially across published docs under `doc/` and key entry surfaces such as `README.md` (English default), `README.zh-CN.md`, `mcp/README.md`, and `mcp/README.zh-CN.md` during periodic maintenance or before preparing corrective PRs.

Documentation and extension workflows derived from local slash commands (docs, explanation, issues, prototypes, tutorials, MCP design review).

Reusable git delivery workflows derived from local slash commands (commit, push, PR, release notes, GitHub Actions failure triage with worktree-based fixes, and isolating your own changes from a shared dirty workspace).

Analyze, standardize, validate, and sync locally maintained skills into agent skill directories with a `skills` CLI-aligned workflow. Use this skill when Codex needs to turn ad-hoc prompt or rules folders into reusable `SKILL.md`-based skills, install or sync one or more local skills from `./skills` into Claude, Cursor, CodeBuddy, Codex, or similar agent directories, or manage local skill path mappings and symlink or copy installation behavior.

Triage, repair, and close MCP attribution issues from the local report API with evidence-driven decisions and isolated Worktrunk worktrees. Use this skill when Codex needs to process `tool` attribution issues and skills-related attribution issues, inspect related runs, decide whether the issue is actionable in `mcp/src` or `config/source/skills`, update attribution fields as `owner=codex`, and then complete the fix loop through GitHub issue tracking, worktree-based code changes, PR submission, and follow-up iteration when the problem is repairable.

Spec and no-spec planning workflows derived from local slash commands (requirements, design, tasks).

Periodically analyze open pull requests for CI failures, code review feedback, and quality issues, then fix them in batch. Use this skill when the user asks to check PR status, triage CI failures, fix review comments, analyze open PRs, or run a scheduled PR health check across the repository.

Use when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or corrective PRs across API contracts, documentation freshness, code quality, and CloudBase skill quality.

Design, improve, and evaluate reusable agent skills with high-quality SKILL.md files, precise trigger descriptions, progressive disclosure, and testable behavior. This skill should be used when users ask to create a new skill, rewrite or review an existing skill, audit a skill collection such as `config/source/skills` for redundancy or overlap, improve skill trigger quality, organize skill references, or evaluate whether a skill should trigger and behave correctly.