ai-model-nodejs
Use this skill for Node.js backend AI via @cloudbase/node-sdk (>=3.16.0) — cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM…
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
$ npx -y skills add TencentCloudBase/CloudBase-AI-Toolkit --skill codebase-audit --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/codebase-auditContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: codebase-audit description: 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. alwaysApply: false
End-to-end workflow: systematically review the entire codebase, report findings as GitHub issues, fix each issue in an isolated git worktree, and submit PRs — all in one session.
Use this skill when you need to:
**Do NOT use for:**
1. Read `references/review-strategy.md` for the review scope and checklist. 2. Use the `code-explorer` subagent to read ALL source files in the target directory (default: `mcp/src/`). 3. For each file, systematically check against the review checklist:
4. Record every finding with: file path, line number(s), category, severity (Critical/High/Medium/Low), description, and suggested fix. 5. **Dependency scan**: Read `references/dependency-audit.md` and run the Dependabot alert fetch + `npm audit` to discover vulnerable dependencies. Record each finding using the dependency-audit format.
1. Read `references/classification.md` for severity definitions and grouping rules. 2. Deduplicate findings — merge instances of the same pattern across files. 3. Group findings into **fix batches** — related issues that should be fixed together in one PR. 4. Assign severity and priority:
5. Present a structured audit report to the user and wait for confirmation before proceeding.
1. Read `references/issue-workflow.md` for issue creation guidelines. 2. For each fix batch (or individual Critical finding), create a GitHub issue:
gh issue create --title "<type>(<scope>): <summary>" --body "<structured body>" --label "<severity>,<category>"
3. Issue body must include: affected files, line numbers, problem description, expected behavior, and suggested fix approach. 4. Link related issues when findings are connected. 5. Present the created issues to the user.
1. Read `references/worktree-fix.md` for the isolation and fix procedure. 2. For each issue (in priority order): a. Create an isolated worktree and branch:
git worktree add ../<repo>-audit-fix-<issue-number> -b fix/<slug>-<issue-number> origin/main
b. Work inside the worktree — never in the main checkout. c. Implement the fix, keeping changes minimal and focused. d. Verify locally: `cd mcp && npm run build && npm run test` e. Commit with conventional-changelog format:
git commit -m 'fix(<scope>): 🔒 <english description>
Closes #<issue-number>'f. Push and create PR:
git push github fix/<slug>-<issue-number>
gh pr create --title "fix(<scope>): 🔒 <summary>" --body "Closes #<issue-number>\n\n<description>" --base maing. Remove the worktree after PR is created:
cd <original-dir>
git worktree remove ../<repo>-audit-fix-<issue-number>3. One worktree per issue. Never mix fixes across worktrees. 4. **Dependency fixes**: For dependency vulnerability batches, follow `references/dependency-audit.md` Step 4. These can be grouped into a single PR since they modify `package.json` / `package-lock.json`.
1. Read `references/verification.md` for the verification checklist. 2. Check CI status for each PR:
gh pr checks <number>
3. If CI fails, re-enter the worktree, fix, and push again. 4. Generate a final audit report summarizing:
| Task | Read | | --- | --- | | What to review and how to check each category | `references/review-strategy.md` | | Security severity classification (TSRC-style) | `references/security-severity-checklist.md` | | How to classify, deduplicate, and batch findings | `references/classification.md` | | How to create well-structured GitHub issues | `references/issue-workflow.md` | | How to create worktrees and fix issues in isolation | `
AI writes the code. CloudBase runs the backend. The CloudBase integration layer for AI coding tools: Plugin installs the stack, Skills steer how code is written, MCP operates databases, functions, storage, and deploys from chat.
Repo: TencentCloudBase/CloudBase-AI-Toolkit
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