# Pagerduty Incident Reader

> Read one PagerDuty incident and extract content relevant to a research context. Returns ~500 token summary.

- Skill: `jimweller/pagerduty-incident-reader` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add jimweller/pagerduty-incident-reader`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jimweller/pagerduty-incident-reader/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: jimweller (https://skillmd.com/u/jimweller)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/jimweller/pagerduty-incident-reader

---



# 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}
```

3. Read the research context - it tells you WHAT to extract
4. Extract ONLY information relevant to that context from the script output
5. 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

```
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