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Ensemble Patrol

skill-o0000-code-cc-workshop-cc-workshop-patrol · by O0000-code

Run a comprehensive QA patrol on the CC Workshop Tauri desktop app. Use when asked to check Tauri project health, run tests, lint code, or audit for issues. Do not use for iOS projects.

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Install

$ agentstack add skill-o0000-code-cc-workshop-cc-workshop-patrol

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

CC Workshop Tauri Project Patrol

Overview

Perform a comprehensive quality audit on the CC Workshop Tauri 2 desktop application, covering both the React frontend and Rust backend.

Workflow

1) Prepare

  • Verify you are in the CC Workshop project directory (CC Workshop2/).
  • Run git fetch origin main to ensure you have the latest state.
  • Note the current branch and HEAD commit for the patrol report.

2) Run Frontend Tests

  • Execute the frontend test suite:

``bash npm run test ``

  • Record: total tests, passed, failed, skipped.
  • If any tests fail, classify as "critical" and note the failing test names.

3) Run Backend Tests

  • Execute the Rust test suite:

``bash cd src-tauri && cargo test ``

  • Record: total tests, passed, failed.
  • If any tests fail, classify as "critical".

4) Frontend Linting

  • Run ESLint on the frontend source:

``bash npx eslint src/ ``

  • Run TypeScript type checking:

``bash npx tsc --noEmit ``

  • Record: total warnings, total errors from both tools.

5) Rust Linting

  • Run Clippy with strict mode:

``bash cd src-tauri && cargo clippy -- -D warnings ``

  • Run format check:

``bash cd src-tauri && cargo fmt -- --check ``

  • Record any warnings or formatting issues.

6) Scan for TODO/FIXME/HACK

  • Search all source files for tech debt markers:

``bash grep -rn "TODO\|FIXME\|HACK\|XXX" src/ --include="*.ts" --include="*.tsx" grep -rn "TODO\|FIXME\|HACK\|XXX" src-tauri/src/ --include="*.rs" ``

  • Count and categorize by type and layer (frontend vs backend).
  • Note files with more than 3 markers as high-priority tech debt.

7) Check Recent Changes

  • Run git log --since=24.hours --oneline to list recent commits.
  • For each commit, review the diff for:
  • Unsafe Tauri IPC calls (not using safeInvoke)
  • Missing error handling in async functions
  • TypeScript any types that should be properly typed
  • Rust unwrap() calls that should use proper error handling
  • Files exceeding 300 lines
  • Record any issues found.

8) Security Audit

  • Run npm security audit:

``bash npm audit --json ``

  • Check for high or critical vulnerabilities.
  • Record findings.

9) Report & Linear Integration

CRITICAL RULES:

  • You MUST actually call the MCP tools. Do NOT fabricate or hallucinate tool call results.
  • If an MCP tool call fails, report the failure honestly. Do NOT pretend it succeeded.
  • Use list_teams to find your team ID. Use list_projects to find the "CC Workshop" project.
  • If the "CC Workshop" project does not exist, create it using save_project with name "CC Workshop" and description "CC Workshop Tauri desktop app - AI-assisted autonomous development workflow".
  • ALWAYS include projectId when creating issues to ensure they are assigned to the correct project.
  • After calling save_issue, check the returned result for the issue ID and URL to confirm success.
If issues are found:

For each issue discovered, create a Linear Issue using the Linear MCP:

Tool: mcp__linear-server__save_issue
Parameters:
  teamId: (use list_teams to find the team ID)
  projectId: (use list_projects to find "CC Workshop" project ID; if not found, create it first with save_project)
  title: "[AI-Patrol] {concise description of issue}"
  description: |
    ## Source
    Discovered by automated patrol on {date}.

    ## Details
    {detailed description of the issue}

    ## Location
    {file path and line numbers}
    Layer: {Frontend / Backend / Both}

    ## Suggested Fix
    {brief suggestion if applicable}
  labelIds: (use list_issue_labels to find IDs for: "CC Workshop" (create if not exists), "Bug" or "Improvement", "ai-discovered", "needs-triage")
  priority: {1=Urgent for test failures, 2=High for build/security issues, 3=Medium for lint errors, 4=Low for TODOs}
If no issues are found:

Output: "No issues found. CC Workshop project is healthy."

Patrol Summary

Generate a structured summary:

## Patrol Report: CC Workshop
- Date: {YYYY-MM-DD HH:MM}
- Status: {healthy / warnings / critical}
- Frontend Tests: {passed}/{total} passed, {failed} failed
- Backend Tests: {passed}/{total} passed, {failed} failed
- ESLint: {N} warnings, {N} errors
- TypeScript: {N} errors
- Clippy: {N} warnings
- TODOs/FIXMEs: {frontend count} frontend, {backend count} backend
- Security: {N} high/critical vulnerabilities
- Recent commits analyzed: {count}
- Issues created: {count}

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.