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When Lark integration tests need running → execute test suite, analyze failures, auto-iterate fixes by severity.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
When prompt, tool, or agent logic changes need regression testing → run eval benchmarks to detect regressions or improvements.
When a task can be parallelized (bulk code review, multi-module refactor, batch analysis) → split into subtasks running in isolated git worktrees via multiple workers.
When the user wants to research academic papers → search ArXiv, extract PDFs, summarize/review/Q&A, generate experiment code.
When you need to interact with web pages using the user's logged-in browser → control Chrome via @playwright/cli daemon, reusing cookies/session with persistent tabs.
When user needs AnyGenIO content generation → unified CLI for task execution with progressive disclosure.
When you need to persist files (reports, docs, evidence) beyond the session → create/query/delete durable artifacts.
| name | self-test |
| description | When Lark integration tests need running → execute test suite, analyze failures, auto-iterate fixes by severity. |
| triggers | {"intent_patterns":["self.?test|自测|场景测试|scenario.?test|run.?test|测试套件","跑.*测试|run.*tests|执行.*测试|execute.*tests","飞书.*测试|lark.*test|集成.*测试|integration.*test","测试.*失败.*修|fix.*failing|修复.*测试|repair.*test","全量.*测试|full.*suite|冒烟.*测试|smoke.*test"],"context_signals":{"keywords":["test","scenario","lark","测试","自测","集成","冒烟","suite","失败","修复"]},"confidence_threshold":0.7} |
| priority | 7 |
| requires_tools | ["bash"] |
| max_tokens | 200 |
| cooldown | 120 |
Run the Lark scenario test suite, analyze failures by root cause (test_drift, prompt_issue, tool_bug, etc.), apply tiered auto-fixes (up to 3 rounds), and generate a structured report. All test execution, failure analysis, and iterative repair logic are handled by run.py.
python3 skills/self-test/run.py run