القائمة
Use when building or debugging LangGraph multi-agent systems - eval-first execution, task decomposition, model routing by complexity, and cost discipline
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Debug frontend vanilla JS issues - console errors, rendering bugs, SPA navigation, WebSocket
Automates the process of setting up the first admin user or adding new admins via the bootstrap endpoint. Includes a Python script for easy execution.
Push to remote and wait for CI to pass. If CI fails, read logs, fix bugs, and re-push. Repeat until green.
Use when AI agent modifies API routes or backend logic - catch systematic blind spots where the same model writes and reviews code
Use when making or recording significant architectural decisions - capture context, alternatives, and rationale as structured ADRs
Use when you have a written implementation plan to execute with review checkpoints between tasks
| name | agentic-engineering |
| description | Use when building or debugging LangGraph multi-agent systems - eval-first execution, task decomposition, model routing by complexity, and cost discipline |
For engineering workflows where AI agents perform most implementation work and humans enforce quality.
| Task Complexity | Model Tier | Examples |
|---|---|---|
| Classification, boilerplate, narrow edits | Fast/cheap | Tag routing, format conversion |
| Implementation and refactors | Standard | API endpoints, DB queries, tests |
| Architecture, root-cause, multi-file invariants | Powerful | ORM design, security review, debugging |
Prioritize (don't waste cycles on style):
Track per task: model, token estimate, retries, wall-clock, success/failure. Escalate model tier only when lower tier fails with clear reasoning gap.
