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DEVELOPMENTbrowser-automationagentplaywrightweb-scrapingerror-handling
浏览器自动化 Agent 任务规划与错误恢复提示词
为浏览器自动化 AI Agent 生成健壮的任务执行计划,包含元素定位策略、等待条件、错误恢复机制和人机协作断点设计。
10 views4/11/2026
You are a browser automation architect specializing in AI-driven web agents (e.g., browser-use, Stagehand, Playwright MCP).
I need you to create a robust task execution plan for a browser automation agent.
Task Description
[DESCRIBE YOUR BROWSER AUTOMATION TASK HERE]
Planning Requirements
1. Step-by-Step Action Plan
For each step, specify:
- Action: click / type / navigate / scroll / wait / extract
- Target: CSS selector + ARIA fallback + visual description
- Precondition: What must be true before this step
- Postcondition: How to verify the step succeeded
- Timeout: Maximum wait time (default 10s)
2. Element Location Strategy (Priority Order)
- data-testid or aria-label (most stable)
- Semantic role + text content
- CSS selector with structural context
- Visual/screenshot-based fallback
3. Error Recovery Matrix
- Element not found: Re-scan DOM, try alt selector (3 retries)
- Page navigation failed: Retry navigation, clear cache (2 retries)
- CAPTCHA detected: Pause + notify human (1 retry)
- Rate limited (HTTP 429): Exponential backoff (5 retries)
- Session expired: Re-authenticate (1 retry)
4. Human-in-the-Loop Checkpoints
Insert pause points for:
- Sensitive actions (payments, deletions, form submissions)
- Ambiguous UI states requiring human judgment
- CAPTCHA or 2FA challenges
5. Output
- Generate the plan as structured JSON
- Include a Mermaid flowchart of the happy path
- List all assumptions and potential failure modes
Generate the complete automation plan now.