/install wangjipeng-log-to-incident-report
Log To Incident Report
Use when (1) user provides error logs and needs structured incident report with root cause. (2) impact. (3) and fix steps.
Core Position
This skill solves the specific engineering problem of: user provides error logs and needs structured incident report with root cause, impact, and fix steps
This skill is NOT:
- A general-purpose capability that activates on anything
- A replacement for manual human judgment
- A tool that stores state or remembers across sessions
This skill IS activated ONLY when the trigger conditions are explicitly met.
Modes
/log-to-incident-report
Default mode. Performs the core task end-to-end.
When to use: User provides input matching the trigger conditions above.
Execution Steps
-
Receive logs — User pastes error logs, stack traces, or system output
- Identify the log format (JSON, plain text, structured key=value)
- Note the time range covered by the logs
- If the input is not error logs, state: "This skill converts error logs into structured incident reports. Please provide error log content."
-
Parse and categorize errors — Extract structured information:
- Identify unique error types and their frequency
- Extract error messages, codes, and stack traces
- Note timestamps to establish an incident timeline
- Determine affected services, endpoints, or components
-
Analyze root cause — Determine what triggered the incident:
- Cross-reference error patterns with timestamps
- Identify the first error in the chain (root cause)
- Note any preceding events that may have contributed
- Distinguish between symptoms and root causes
-
Assess impact — Quantify the scope of the incident:
- How many users/requests were affected (if derivable from logs)
- Which services or systems were impacted
- Duration of the incident (first error to recovery)
-
Generate incident report — Produce the structured document:
- Incident Summary: one-paragraph overview
- Timeline: chronological sequence of events
- Root Cause: what caused the incident
- Impact: scope and severity of the incident
- Mitigation Steps: what was done to resolve it
- Action Items: follow-up tasks to prevent recurrence
-
Deliver with confidence level — State any assumptions or uncertainties:
- If root cause is unclear, state "Root cause analysis based on available logs; further investigation may be needed"
- If impact cannot be determined from logs, state what is unknown
Mandatory Rules
Do not
- Do not make up facts or claim actions were taken that were not
- Do not hardcode API keys — use
os.getenv("API_KEY")instead - Do not store sensitive user data beyond the current session
- Do not exceed token budget without warning the user first
- Do not activate for off-topic requests — return a brief decline message
Do
- Validate all inputs before acting
- Handle errors gracefully with actionable error messages
- Log actions taken for auditability
- State explicitly when you are uncertain or data is insufficient
Quality Bar
A good output:
- Solves exactly the problem described in the trigger conditions
- Provides actionable result in the expected format within 3 turns
- Handles error cases with specific guidance, not generic "try again"
- States assumptions explicitly when input is ambiguous
A bad output:
- Solves a different problem than the one triggered
- Provides a generic "I can't help with that" without explaining why
- Crashes, hangs, or returns malformed output on valid input
- Activates for off-topic requests (false positive)
Good vs. Bad Examples
| Scenario | Bad Output | Good Output |
|---|---|---|
| Trigger matched | "I can help with that." + no action | Correct transformation delivered in structured format |
| Invalid input | Crash or wrong result | "Missing required field: [X]. Please provide [Y]." |
| Ambiguous input | Guesses and might be wrong | States assumption and asks for confirmation |
| Off-topic request | Attempts to help anyway | "This skill activates when [trigger]. Please restate your request." |
References
references/— Detailed templates, schemas, and edge-case rules for this skill
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install wangjipeng-log-to-incident-report - 安装完成后,直接呼叫该 Skill 的名称或使用
/wangjipeng-log-to-incident-report触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
log-to-incident-report 是什么?
Use when (1) user provides error logs and needs structured incident report with root cause. (2) impact. (3) and fix steps. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 35 次。
如何安装 log-to-incident-report?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install wangjipeng-log-to-incident-report」即可一键安装,无需额外配置。
log-to-incident-report 是免费的吗?
是的,log-to-incident-report 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
log-to-incident-report 支持哪些平台?
log-to-incident-report 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 log-to-incident-report?
由 王继鹏(@wangjipeng977)开发并维护,当前版本 v1.0.0。