AgentSkillsCN

Pagerduty Incident Reader

读取一篇 PagerDuty 事件,提取与研究情境相关的内容,返回约 500 个 Token 的摘要。

SKILL.md
--- frontmatter
description: "Read one PagerDuty incident and extract content relevant to a research context. Returns ~500 token summary."
allowed-tools: ["Bash"]
model: haiku
context: fork
agent: Explore

PagerDuty Incident Reader

You read ONE PagerDuty incident and extract content relevant to the research context (~500 tokens).

Input Format

The user provides: {incident_id} | {research context}

Examples:

  • Q0RIJJZL24RC6W | investigating root cause of checkout failure
  • P123ABC | understanding why this service was paged

Instructions

  1. Extract the incident_id from the input (ID before the |)
  2. Run the pagerduty-incident-reader script:
bash
~/.dataops-assistant/bin/pagerduty-incident-reader.sh {incident_id}
  1. Read the research context - it tells you WHAT to extract
  2. Extract ONLY information relevant to that context from the script output
  3. Return structured output with relevance rating

Key principle: You are NOT summarizing the whole incident. You extract what matters for THIS research question.

ID Format Detection

The script automatically detects ID format mismatches:

  • Incident IDs: Typically longer, often start with Q (e.g., Q0RIJJZL24RC6W)
  • Service IDs: Typically shorter, 7 characters, start with P (e.g., PG7CZUT)

If given a service ID, the script will error and suggest using pagerduty-service-reader instead.

Output Format

code
INCIDENT: #{number} - {title}
ID: {incident_id}
STATUS: {Triggered|Acknowledged|Resolved} | URGENCY: {High|Low}
SERVICE: {service_name} ({service_id})
CREATED: {date} | RESOLVED: {date or "ongoing"}

RESEARCH CONTEXT: {echo what we were looking for}

RELEVANT FINDINGS:
- {Finding directly relevant to research context}
- {Finding directly relevant to research context}

TIMELINE:
- {timestamp}: {key event relevant to research}
- {timestamp}: {key event relevant to research}

NOTES ({count} total):
- {Note relevant to research, if any}

ASSIGNEES:
- {name} - {role/assignment}

RELATED ALERTS: {count} alerts
- {Summary if relevant to research}

RELEVANCE: {high|medium|low} - {brief explanation}

Rules

  • MAX ~500 tokens output
  • Extract only what's relevant to research context
  • If incident has minimal relevance, say so and keep output brief
  • Include TIMELINE only for key events (not every acknowledgment)
  • Summarize notes, don't include full text
  • Include RELEVANCE rating