Postmortem Writer

    1

    Transforms incident logs and alert timelines into blameless, evidence-backed postmortem reports.

    $39

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    Postmortem Writer

    Example session with this skill installed

    Draft a postmortem for the API outage yesterday. Here is the Slack export from #incident-api-104 and the PagerDuty alert timeline. Focus on why the auto-scaler failed to trigger.

    • Read your context and instructions
    • Compiled the postmortem writer

    I have analyzed the Slack transcript and PagerDuty events. I normalized 42 events into a UTC timeline and identified a 12-minute gap between the first 5xx spikes and the initial page.

    Incident Report: API Scaling Failure (SEV-2)

    Summary: The production API experienced 100% error rates for 18 minutes due to an auto-scaler configuration lockout.

    MetricValue
    MTTD4m 12s
    MTTA2m 45s
    MTTR18m 22s
    SeveritySEV-2

    Timeline Summary

    • 2023-10-12 14:02:10 UTC: First 503 errors detected in ap-southeast-2.
    • 2023-10-12 14:06:22 UTC: PagerDuty alert #882 fired (High Urgency).
    • 2023-10-12 14:09:07 UTC: On-call engineer acknowledged alert.
    • 2023-10-12 14:15:30 UTC: Root cause identified: Terraform lock held by stale CI job prevented scaling.
    • 2023-10-12 14:20:32 UTC: Manual lock release; scaling resumed.

    Root Cause Analysis

    • Trigger: Sudden traffic spike exceeded current node capacity.

    Root Cause: A failed CI pipeline left a global state lock on the production workspace, preventing the auto-scaler from updating the desired instance count.

    Contributing Factor: The auto-scaler's health check did not alert when Terraform operations failed due to locking.

    Action Items

    • Prevents: Implement 10-minute TTL on Terraform state locks. (Owner: Platform Team)
    • Detects: Add CloudWatch alarm for ScalingFailed events in the provider log. (Owner: SRE)
    • Mitigate: Document manual state unlock procedure in the emergency runbook. (Owner: On-call)

    Next steps

    1. Review the 4-minute gap between error spikes and the PagerDuty alert; the threshold may be too high.
    2. Assign owners and due dates to the action items above.
    3. Verify if the stale CI job (13:45 UTC) is a recurring failure.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Engineering teams lose hours manually reconstructing incident timelines from Slack logs and PagerDuty alerts. These documents often suffer from subjective bias, blame-coded language, and metrics that don't actually match the evidence.

    What it does

    • Normalizes and merges timestamps from Slack, PagerDuty, and log files into a single UTC timeline.
    • Calculates precise MTTD, MTTA, and MTTR metrics directly from tagged incident events.
    • Identifies the technical trigger, root cause, and contributing factors using blameless 5-Whys analysis.
    • Generates a structured Markdown report with categorized action items (prevents, detects, mitigates).
    • Flags timeline gaps and unsupported causal claims for human verification.

    Frameworks & tools

    Python-based scripts for timeline parsing and report rendering. Supports JSON exports from Slack, PagerDuty, and Opsgenie, plus CSV and plain text logs.

    Why this beats prompting it yourself

    Generic LLMs often hallucinate timestamps or "guess" root causes when data is missing. This skill enforces strict evidence-based drafting, ensuring every claim in the report is backed by a specific entry in the normalized timeline while strictly maintaining a blameless engineering culture.

    Use cases

    • Drafting SEV1/SEV2 root cause analysis documents after a system outage.
    • Auditing human-written postmortems for timeline gaps or blame-heavy language.
    • Converting messy incident Slack channels into readable executive summaries.
    • Generating standardized incident metrics for quarterly reliability reviews.

    Known limitations

    Does not connect directly to external APIs. Users must provide text or JSON exports of incident data. Does not perform automated code-level debugging.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scanned

    Verified clean 1 month ago

    • Passed all security checks, Safe to install

    Requires

    Python

    Listed1 month ago

    What's inside

    Frequently Asked Questions