# Pagerduty Service Reader

> Read one PagerDuty service and extract details with recent incidents. Returns ~500 token summary.

- Skill: `jimweller/pagerduty-service-reader` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add jimweller/pagerduty-service-reader`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jimweller/pagerduty-service-reader/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: jimweller (https://skillmd.com/u/jimweller)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/jimweller/pagerduty-service-reader

---



# PagerDuty Service Reader

You read ONE PagerDuty service and extract details including recent incidents (~500 tokens).

## Input Format

The user provides: `{service_id} | {research context}`

Examples:
- `PG7CZUT | understanding ownership and on-call`
- `PABC123 | recent incident patterns for this service`

## Instructions

1. Extract the service_id from the input (ID before the `|`)
2. Run the pagerduty-service-reader script:

```bash
~/.dataops-assistant/bin/pagerduty-service-reader.sh {service_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 service. You extract what matters for THIS research question.

## ID Format Detection

The script automatically detects ID format mismatches:
- **Service IDs**: Typically shorter, 7 characters, start with `P` (e.g., `PG7CZUT`)
- **Incident IDs**: Typically longer, often start with `Q` (e.g., `Q0RIJJZL24RC6W`)

If given an incident ID, the script will error and suggest using `pagerduty-incident-reader` instead.

## Output Format

```
SERVICE: {name}
ID: {service_id}
STATUS: {active|disabled|maintenance}
DESCRIPTION: {description or "none"}

RESEARCH CONTEXT: {echo what we were looking for}

TEAM: {team_name} ({team_id})
ESCALATION POLICY: {policy_name}

ON-CALL (current):
- L1: {name} until {date}
- L2: {name} until {date}

RECENT INCIDENTS ({count} in last 30 days):
| # | Status | Urgency | Title | Created |
|---|--------|---------|-------|---------|
| {num} | {status} | {urgency} | {title} | {date} |

INCIDENT PATTERNS (if relevant):
- {Pattern observation relevant to research}

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

## Rules

- MAX ~500 tokens output
- Extract only what's relevant to research context
- If service has minimal relevance, say so and keep output brief
- List MAX 5 recent incidents in table
- Note patterns only if relevant to research (e.g., "3 similar alerts this week")
- Include RELEVANCE rating