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    Launchguard Production Auditor

    1

    Automated production readiness auditor for software projects with evidence-based scoring and remediation plans.

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    Launchguard Production Auditor

    Launchguard Production Auditor

    Example session with this skill installed

    Audit the attached Node.js/Postgres repository for production readiness. We plan to deploy to AWS via Docker next week. Give me a full report and a verdict.

    • Read your context and instructions
    • Compiled the launchguard production auditor

    I have completed the production readiness audit for the project. The stack is identified as a Node.js (Express) API using TypeORM with PostgreSQL, targeting a Dockerized deployment.

    Verdict: NO-GO
    Readiness Score: 62/100

    Top Blockers

    • LG-SEC-01 (CRITICAL): Hardcoded PostgreSQL password in src/config/database.ts.
    • LG-MIG-03 (HIGH): Destructive DROP COLUMN in migration 16928340-update-users.sql without data backup.
    • LG-ENV-02 (HIGH): Missing validation for JWT_SECRET which will cause runtime crashes if not set.

    Audit Findings

    IDDomainSeverityLocationSummary
    LG-SEC-01SecretsCRITICALsrc/config/database.ts:12Hardcoded DB password dbpa****(12 chars).
    LG-MIG-03MigrationsHIGHmigrations/*.sqlDestructive schema change on the users table.
    LG-ENV-02EnvironmentHIGHsrc/index.ts:5Startup does not check for required JWT env vars.
    LG-HLT-01HealthMEDIUMproject-wideMissing /healthz or liveness probes for Docker.
    LG-CFG-01ConfigLOWpackage.jsonStart script uses nodemon instead of node.

    Per-Domain Results

    • Auth & Authorization: PASS. Routes use Passport.js middleware correctly.
    • API Error Handling: PASS. Centralized error handler prevents stack trace leaks.
    • Logging: CONDITIONAL. Console logging used; recommend structured JSON for CloudWatch.
    • Backup & Rollback: FAIL. No rollback scripts detected in the migration directory.

    Next steps

    1. Rotate the compromised PostgreSQL password immediately at the database level.
    2. Wrap the DROP COLUMN migration in a transaction with a pre-migration data export task.
    3. Implement a startup validation script for all environment variables using a schema library like Zod.

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

    About this skill

    Software projects fail in production because of environment mismatches, leaked secrets, and destructive migrations. This skill acts as a senior release engineer to audit your codebase for launch risks before your users find them. It delivers an evidence-based verdict backed by a prioritized remediation plan.

    What it does

    Secrets detection identifies hardcoded credentials, API keys, and connection strings with masked evidence.

    Production readiness scoring calculates a GO, CONDITIONAL GO, or NO-GO verdict based on critical and high-severity risks.

    Migration safety analysis flags destructive database operations that cause downtime or data loss during deployment.

    Environment validation maps required variables against your configuration to find missing production keys.

    Infrastructure audit reviews Dockerfiles, CI/CD configs, and manifest files for insecure defaults and dev-only settings.

    How it works

    Scope detection identifies your framework, database, and hosting target from the project tree. Automated pre-scan searches for leads across secrets, dependencies, and build scripts. Deep domain audit evaluates the project against 12 risk domains including Auth, API handling, and Observability. Verdict delivery generates a structured report with prioritized fixes and verification steps.

    Frameworks & tools

    Works with any stack including Node.js, Next.js, Python, Go, and Rust. It understands deployment targets like Docker, Kubernetes, Vercel, AWS Lambda, and Fly.io.

    Why this beats prompting it yourself

    Generic prompts miss framework-specific edge cases like Next.js public environment variable leaking or non-idempotent SQL migrations. This skill follows a rigorous 12-domain checklist and scoring system that prevents "hallucinated" readiness.

    Use cases

    Auditing a repository before a major version release to production.

    Reviewing a junior developer's PR for security gaps and hardcoded mocks.

    Generating a production-readiness report for stakeholders or compliance needs.

    Hardening a Dockerized application against root-user and open-port vulnerabilities.

    Known limitations

    Cannot verify external cloud provider settings, DNS records, or secrets manager contents not present in the repository. Does not execute code or perform live penetration testing.

    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.

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    Trust & safety

    Security scanned

    Verified clean 16 days ago

    • Passed all security checks, Safe to install

    Requires

    Python

    Listed16 days ago

    What's inside

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