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 233i/agent-skills --skill debugging-and-error-recoverygit clone --depth 1 https://github.com/233i/agent-skillsWrote 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/233i/agent-skills/debugging-and-error-recovery)<a href="https://agentmods.dev/skills/233i/agent-skills/debugging-and-error-recovery"><img src="https://agentmods.dev/badge/skills/233i/agent-skills/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/233i/agent-skills/debugging-and-error-recovery"><img src="https://agentmods.dev/badge/skills/233i/agent-skills/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 | $0.00064 | $0.02661 |
| Opus 5 | $0.00032 | $0.01331 |
| Sonnet 5 | $0.00013 | $0.00532 |
| Haiku 4.5 | $0.00006 | $0.00266 |
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 8d 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
用结构化分诊来进行系统化调试。当某个地方坏掉时,先停止加功能,保留证据,然后按固定流程找出并修复根因。靠猜只会浪费时间。这套分诊清单适用于测试失败、构建错误、运行时 bug 以及生产事故。
何时使用
- 代码改完后测试失败
- 构建损坏
- 运行时行为与预期不符
- 收到 bug 报告
- 日志或控制台里出现错误
- 某个本来能工作的东西突然不能用了
Stop-the-Line 规则
当任何不符合预期的事情发生时:
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
不要一边顶着失败测试或损坏构建,一边继续做下一个功能。 错误会叠加。第 3 步里的 bug 如果没修,就会让第 4-10 步全都建立在错误基础上。
分诊清单
按顺序完成这些步骤,不要跳步骤。
步骤 1:复现
让失败稳定地发生。如果无法稳定复现,你就无法有把握地修好它。
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 无法稳定复现时:
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:
# 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.
- 8d ago First seen · 301 lines · 64 tokens per session scan A d3906f7695e2
debugging-and-error-recovery is a skill published in the GitHub repository 233i/agent-skills (6 stars, last pushed 5mo ago), licensed MIT. It adds 64 tokens to every session and 2,661 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
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