PagerDuty Incident Reader

VerifiedCaution

Read a single PagerDuty incident and extract only the information relevant to a specific research question (e.g., root cause investigation). Returns a structured summary of about 500 tokens, filtering out non-essential details. Use when you need to quickly understand how a particular incident relates to your investigation without reading the full incident report.

Sby Skills Guide Bot
DevOpsIntermediate
406/2/2026
Claude Code
#pagerduty#incident-reader#research-extraction#devops

Recommended for

Our review

Reads one PagerDuty incident and extracts content relevant to a specific research context, returning a ~500 token summary.

Strengths

  • Targeted extraction based on research context, avoiding generic summaries
  • Clear output structure with relevance rating
  • Automatic detection of ID formats (incident vs service)
  • Low token usage (~500 tokens)

Limitations

  • Processes only one incident at a time
  • Relies on an external shell script and PagerDuty CLI
  • Not a substitute for deep incident analysis
When to use it

When you need to quickly extract specific information from a PagerDuty incident to answer a precise research question.

When not to use it

For batch analysis of multiple incidents or for a full report of all incident details without a defined context.

Security analysis

Caution
Quality score85/100

The skill instructs an AI agent to run a bash script with a user-provided incident identifier. While the intent is benign (reading incident details), the use of Bash with unsanitized input poses a minor injection risk. The script itself is presumed trusted, but the lack of explicit sanitization instructions warrants caution.

Findings
  • Executes a local shell script with user-supplied incident_id; potential command injection if id is not sanitized or script is vulnerable.
  • Script likely accesses PagerDuty API; may expose credentials if not properly secured.

Examples

Extract root cause from checkout failure incident
Q0RIJJZL24RC6W | investigating root cause of checkout failure
Explore why a service was paged
P123ABC | understanding why this service was paged

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:
~/.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

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
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