Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vinvcn/addyosmani-agent-skills-zh --skill debugging-and-error-recoverygit clone --depth 1 https://github.com/vinvcn/addyosmani-agent-skills-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vinvcn/addyosmani-agent-skills-zh/debugging-and-error-recovery)<a href="https://agentmods.dev/skills/vinvcn/addyosmani-agent-skills-zh/debugging-and-error-recovery"><img src="https://agentmods.dev/badge/skills/vinvcn/addyosmani-agent-skills-zh/debugging-and-error-recovery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vinvcn/addyosmani-agent-skills-zh/debugging-and-error-recovery"><img src="https://agentmods.dev/badge/skills/vinvcn/addyosmani-agent-skills-zh/debugging-and-error-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.02674 |
| Opus 5.5 | $0.00031 | $0.01070 |
| Sonnet 5.5 | $0.00016 | $0.00535 |
| Haiku 4.5 | $0.00008 | $0.00267 |
Grade A, and why
debugging-and-error-recovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
调试与错误恢复
概览
用结构化 triage 进行系统化调试。当某样东西出错时,停止添加功能,保存证据,并按结构化流程找到并修复根因。猜测只会浪费时间。这份 triage checklist 适用于测试失败、构建错误、运行时 bug 和生产事故。
何时使用
- 代码改动后测试失败
- 构建中断
- 运行时行为不符合预期
- 收到 bug report
- 日志或 console 中出现错误
- 之前能正常工作的东西突然不能用了
Stop-the-Line 规则
当出现任何意外情况时:
1. STOP adding features or making changes
2. PRESERVE evidence (error output, logs, repro steps)
3. DIAGNOSE using the triage checklist
4. FIX the root cause
5. GUARD against recurrence
6. RESUME only after verification passes
不要带着失败测试或破损构建继续去做下一个功能。 错误会叠加。第 3 步中未修复的 bug 会让第 4-6 步全部出错。
Triage Checklist
按顺序完成这些步骤。不要跳步。
第 1 步:复现
让失败稳定地发生。如果无法复现,就无法有把握地修复。
Can you reproduce the failure?
├── YES → Proceed to Step 2
└── NO
├── Gather more context (logs, environment details)
├── Try reproducing in a minimal environment
└── If truly non-reproducible, document conditions and monitor
当 bug 无法复现时:
Cannot reproduce on demand:
├── Timing-dependent?
│ ├── Add timestamps to logs around the suspected area
│ ├── Try with artificial delays (setTimeout, sleep) to widen race windows
│ └── Run under load or concurrency to increase collision probability
├── Environment-dependent?
│ ├── Compare Node/browser versions, OS, environment variables
│ ├── Check for differences in data (empty vs populated database)
│ └── Try reproducing in CI where the environment is clean
├── State-dependent?
│ ├── Check for leaked state between tests or requests
│ ├── Look for global variables, singletons, or shared caches
│ └── Run the failing scenario in isolation vs after other operations
└── Truly random?
├── Add defensive logging at the suspected location
├── Set up an alert for the specific error signature
└── Document the conditions observed and revisit when it recurs
对于测试失败(示例用 npm,请替换成本仓库自己的测试命令,参见 test-driven-development skill 中 Discover the Stack First 一节):
# Run the specific failing test
npm test -- --grep "test name"
# Run with verbose output
npm test -- --verbose
# Run in isolation (rules out test pollution)
npm test -- --testPathPattern="specific-file" --runInBand
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +21 tokens per session 199622dc1d0a
- 1mo ago First seen · 301 lines · 57 tokens per session scan A 0dad8da52407
debugging-and-error-recovery is a skill published in the GitHub repository vinvcn/addyosmani-agent-skills-zh (44 stars, last pushed 7d ago), licensed MIT. It adds 78 tokens to every session and 2,674 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
debugging-and-error-recovery
Guides systematic root-cause debugging with hard rules against guess-fixes and symptom suppression. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Triggers on "this is broken", "tests are failing", "why doesn't this work", or any error output.
observability-and-instrumentation
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high…
performance-optimization
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
debugging-and-error-recovery
Guides systematic root-cause debugging. Use when tests fail, builds break, something that worked yesterday broke, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need to figure out what broke and why — a systematic approach to finding and fixing the root cause rather than…
error-handling
Graceful degradation and meaningful error messages. Errors are first-class citizens, not afterthoughts. Every error path is designed, not discovered.