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    Incident Postmortem Repoter

    1

    Incident Analysis & RCA Assistant . Turn raw logs and incident notes into structured, blameless postmortems and actionable follow-up items.

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    Incident Postmortem Repoter

    Incident Postmortem Repoter

    Example session with this skill installed

    I have these notes: 14:00 API latency spiked. 14:05 PagerDuty triggered for DB. 14:15 Devs found a locked table from a migration. 14:20 Migration killed, service restored. Generate a postmortem.

    • Read your context and instructions
    • Compiled the incident postmortem repoter

    I have compiled the incident data into a structured postmortem focusing on the database contention issue.

    Incident Postmortem: API Latency Spike (DB Lock)

    1. Executive Summary

    On [Date], the API experienced a significant latency spike due to a database table lock caused by a manual migration. The incident lasted approximately 20 minutes, resulting in degraded service for all API consumers. Service was restored by terminating the offending process.

    2. Incident Details

    • Service: Core API / Production Database
    • Severity: High
    • Status: Resolved
    • Duration: 20 minutes (14:00 - 14:20)

    3. Timeline

    TimeEventSourceSignificance
    14:00API latency spike detectedMonitoringFirst signal of degradation
    14:05PagerDuty Alert: DB High LoadAlertingOfficial detection/escalation
    14:15Identification of locked tableTeam ObsRoot cause identified (Migration)
    14:20Process terminatedMitigationService restoration

    4. Root Cause Analysis

    • Trigger: Execution of a database migration.
    • Immediate Cause: A heavy-write migration locked a high-traffic table.
    • Systemic Cause: Lack of automated migration guardrails or dry-run requirements for production schemas.

    5. Corrective & Preventive Actions

    PriorityActionProblem AddressedVerification
    P0Implement migration timeoutsLong-running locksConfig audit
    P1Update migration runbookLack of pre-flight checksDocumentation PR
    P2Add lock-contention alertsDelayed detectionAlert test in staging

    Next steps

    • Verify if any data corruption occurred during the forced termination.
    • Schedule a review of the migration script that triggered the lock.
    • Assign owners to the P0 and P1 actions listed above.

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

    About this skill

    The problem

    Engineering teams often struggle to produce objective, blameless postmortems after an outage. Manually reconciling messy Slack logs, monitoring alerts, and conflicting timestamps leads to vague reports that fail to prevent future incidents.

    What it does

    • Synthesizes raw incident logs, alert messages, and team observations into a structured postmortem.
    • Constructs a chronological event timeline that flags conflicting timestamps and identifies the first abnormal signal.
    • Performs a multi-layered Root Cause Analysis identifying triggers, contributing factors, and systemic gaps.
    • Generates a prioritized table of actionable follow-up tasks with specific verification methods.
    • Drafts internal and customer-facing incident communications based on verified facts only.

    Why this beats prompting it yourself

    This skill enforces a strict blameless culture, focusing on system failures rather than human error. It prevents the common AI habit of hallucinating metrics or timestamps by explicitly labeling unknowns and requiring evidence-based causality.

    Use cases

    • Transforming a chaotic "war room" Slack export into a professional engineering report.
    • Conducting a 5 Whys analysis to move beyond the immediate trigger to the systemic cause.
    • Creating customer-facing status page updates that balance transparency with security.
    • Auditing monitoring gaps to determine why automated alerts failed to trigger.

    Known limitations

    It cannot verify the truth of provided logs or invent missing data. Qualitative impact assessment requires user-provided metrics.

    Does not support automated log fetching from external APIs. Cannot invent timestamps or quantitative impact metrics if they are not provided in the input.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed1 month ago

    What's inside

    Frequently Asked Questions

    The skill takes raw inputs like Slack war-room exports, monitoring alerts, and team notes to generate a structured timeline, a multi-layered Root Cause Analysis (RCA), and a prioritized list of action items.

    By design, the skill ignores individual blame and focuses on systemic gaps, infrastructure weaknesses, and process failures to ensure the output aligns with modern SRE best practices.

    This skill is a plug-and-play logic module compatible with major LLM-based agents; simply import the skill into your preferred AI workspace and provide your incident data to begin.

    You receive the full Incident Postmortem logic, structured templates for internal and external reports, and the RCA framework, along with documentation on how to format your raw logs for best results.

    Yes, while it produces detailed internal engineering docs, it also generates a separate, high-level summary suitable for customer-facing status pages or executive briefs.

    The skill is designed to flag conflicting timestamps or data gaps rather than guessing; if information is missing from your logs, the report will explicitly mark those areas for human verification.

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