Individual skill
mini-program-debugging-skill
Diagnose and fix mini-program failures through reproducible, evidence-driven root-cause analysis across source, state, asynchronous timing, caches, mock data, build versions, platform behavior, devices, cloud calls, and external services. Use when users report white screens, crashes, stale or jumping values, missing data, intermittent behavior, permission failures, performance stalls, device-only defects, API or cloud-function errors, source-versus-build mismatches, or regressions whose cause is not yet established. Freezes the observation environment, ranks competing hypotheses, runs discriminating checks, creates a failing regression test before repair, covers analogous states, and never hides a known failure with longer waits, swallowed errors, forced success, or cosmetic patches.
skills/mini-program-debugging-skill/SKILL.md
Source commit 2b7f9cb24f142125189b8757fcea489546d76ba7
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Instructions only
- Last checked
- Nov 4, 2026
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Repository context
- Repository stars (not skill ratings)
- 95
- Repository last updated
- Nov 3, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- mini-program Repository topic
- software-engineering Repository topic
- wechat-mini-program Repository topic
- codex-skills Repository topic
- evidence-first Repository topic
- release-readiness Repository topic
- alipay Repository topic
- ci-cd Repository topic
- testing Derived category
- data Derived category
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Browse files
SKILL.mdcore · 5,456 bytesagents/openai.yamlasset · 292 bytesassets/debugging-report.mddoc · 1,251 bytesreferences/debugging-workflow.mddoc · 5,002 bytesreferences/interruption-recovery-protocol.mddoc · 3,522 bytes
Read excerpt
# /mini-program-debugging-skill — 小程序问题调试
从可重复症状建立证据链,定位能解释关键现象的根因,再以失败复现、最小修复和回归测试闭环。诊断请求本身不授权修改;用户要求修复或任务明确包含修复时,才进入受控改动。
## 输入与观察基线
- 接收症状、截图/视频、日志、错误码、复现步骤、项目事实图或失败测试。
- 先固定源码/构建版本、分支/文件状态、运行环境、设备/工具、账号/数据状态、网络与时间,再写最小复现和预期/实际差异。
- 截图是现象证据,不是根因;历史日志不能证明当前构建仍有同一问题。
- 若只有产品语义争议而非故障,退回产品规格;若根因已证实且只需实施,可交给实现阶段。
## 证据驱动调试流程
1. 用最少步骤稳定复现;无法稳定复现时记录频率、前置状态、成功/失败样本和最后正常版本。