Post Incident Record (PIR)

Discover issues from PagerDuty, Datadog, Cloudflare, and Rollbar concurrently, auto-determine severity, and produce completed PIR forms for each issue.

Inputs

Raw arguments: $ARGUMENTS

Infer from the arguments:

• QUERY: what to investigate. Passed directly to each sub-skill. Defaults to "incidents today".
• CF_DOMAIN_ZONE: (optional) Cloudflare domain and zone ID in domain:zone_id format. Passed to the cloudflare-traffic-investigator skill. If not provided, the cloudflare skill will ask the user.

PIR Form Fields

Each PIR maps to these fields — see PIR Form Fields for format, examples, and output template:

Field	Required	Source
Impact Summary	Yes	Synthesised from all skills
What	Yes	PagerDuty incident + Datadog + Cloudflare
Who	Yes	Datadog (RUM/error tracking) + Cloudflare (user counts)
Culprit	Yes	Cloudflare (JA4, traffic sources) + Datadog (error traces) + Rollbar (stack traces, error-deploy correlation) + PagerDuty (trigger details) + Codebase analysis (culprit commits)
Incident date	Yes	Earliest detection across all sources (PagerDuty, Datadog, Cloudflare)
When	Yes	PagerDuty created/resolved + Datadog timeline
Remediation	Optional	PagerDuty notes + Datadog monitors
Incident controller	Optional	PagerDuty escalation policy responders

Severity Auto-Classification

Determine severity from the collected data — do NOT ask the user:

Severity	Criteria
SEV1	Service outage or >50% error rate on critical path; cascading failures; >30 min duration
SEV2	Partial degradation; 10-50% error rate; single service affected; 10-30 min duration
SEV3	Minor impact; <10% error rate; brief spike (<10 min); limited user impact

Use the highest applicable severity when multiple criteria match.

Execution

Step 1: Prepare

See step1-gather-date-range.md — If QUERY is empty, ask the user what to investigate. Otherwise proceed directly.

Step 2: Discover — PagerDuty, Datadog, Cloudflare, Rollbar

Run all four in parallel (each sub-skill uses context: fork for isolation):

2a. PagerDuty — Incidents

See step2a-discover-incidents.md — Invokes Skill("pagerduty-oncall").

2b. Datadog — Observability Data

See step2b-discover-datadog.md — Invokes Skill("datadog-analyser").

2c. Cloudflare — Traffic Analysis

See step2c-discover-cloudflare.md — Invokes Skill("cloudflare-traffic-investigator"). Passes domain and zone ID from CF_DOMAIN_ZONE if provided.

2d. Rollbar — Error Tracking

See step2d-discover-rollbar.md — Invokes Skill("rollbar-reader").

Step 3a: Codebase Analysis

See step3a-codebase-analysis.md — Task subagent. Analyses git history across working directories, correlates with incident timeline from discovery reports.

Step 3b: Generate PIR via NotebookLM

See step3b-generate-nlm.md — Task subagent. Runs after 3a. Creates NotebookLM notebook, uploads all discovery and codebase reports, generates report, infographic, and slide deck. Returns notebook ID.

Step 4: Present Results and Clean Up

See step4-present-results.md — Displays PIR summary, provides notebook link for interactive exploration, cleans up temporary discovery folders. Preserves the NotebookLM notebook for further queries.