Pre-Deploy Blast Radius

    1

    Before you ship: how bad is it if this goes wrong, and who finds out?

    Free

    0 installsSecurity scanned

    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    See it in action

    You say

    I'm about to run 'DROP COLUMN legacy_user_id' on the users table in production. Is this safe to ship?

    Your agent does

    Verdict: ship it with the mitigation below

    Worst realistic outcome: Application errors if any cached queries or background jobs still reference the column. Reversible?: Not reversible. Dropping a column deletes data immediately. What detects it: Sentry/Error logs. Immediate. Ten-minute mitigation: Rename the column first or verify zero references in logs.

    Not checked: Data volume or lock duration.

    About this skill

    The problem

    Developers often ship changes without a clear understanding of the potential fallout if a deployment fails. Standard code reviews focus on logic, but they rarely quantify the "blast radius" or identify how long a failure will go unnoticed.

    What it does

    • Evaluates the worst-case scenario for a specific code fragment, dependency bump, or database migration.
    • Categorizes reversibility into three clear tiers: instant rollback, rollback with manual repair, or permanent loss.
    • Identifies the specific monitoring signals that will trigger on failure and estimates the time to detection.
    • Suggests a single, high-impact mitigation that can be implemented in under ten minutes to shrink the risk profile.

    Why this beats prompting it yourself

    General-purpose LLMs tend to be overly optimistic or provide vague "could cause issues" warnings. This skill enforces a cynical, risk-first methodology that prioritizes silent failures over loud ones and forces an honest assessment of whether a customer or a monitor will find the bug first.

    Use cases

    • Pre-deploy risk check for a critical database schema migration.
    • Quick blast-radius assessment before merging a major dependency version bump.
    • Sanity check for manual production statements or feature flag toggles.
    • Identifying gaps in observability before shipping high-traffic API changes.

    Known limitations

    This is a rapid risk estimate, not a security or performance audit. It requires the user to state assumptions about scale if row counts or traffic volumes are not provided.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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