Babysitter tech-stack-scanner

Automated technical architecture review, security assessment, scalability analysis

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/business/venture-capital/skills/tech-stack-scanner" ~/.claude/skills/a5c-ai-babysitter-tech-stack-scanner && rm -rf "$T"

manifest: library/specializations/domains/business/venture-capital/skills/tech-stack-scanner/SKILL.md

Tech Stack Scanner

Overview

The Tech Stack Scanner skill provides automated technical architecture review for venture capital due diligence. It assesses technology choices, infrastructure scalability, security posture, and technical debt to inform investment decisions.

Capabilities

Architecture Assessment

Evaluate technology stack choices
Assess microservices vs. monolith architecture
Review database and data store choices
Analyze API design and integration patterns

Infrastructure Review

Evaluate cloud infrastructure (AWS, GCP, Azure)
Assess scalability and auto-scaling capabilities
Review disaster recovery and backup strategies
Analyze infrastructure costs and efficiency

Security Assessment

Review authentication and authorization
Assess data encryption practices
Check for common vulnerabilities
Evaluate security monitoring and incident response

Scalability Analysis

Model load handling capabilities
Identify potential bottlenecks
Assess horizontal vs. vertical scaling
Review performance optimization practices

Usage

Scan Tech Stack

Input: Company technical documentation, access credentials
Process: Automated scanning, architecture analysis
Output: Tech stack assessment, architecture diagram

Assess Security Posture

Input: Security policies, system access
Process: Security scanning, policy review
Output: Security assessment, vulnerability report

Evaluate Scalability

Input: Current load, growth projections, infrastructure
Process: Load modeling, bottleneck analysis
Output: Scalability assessment, recommendations

Review Infrastructure Costs

Input: Cloud billing data, infrastructure inventory
Process: Cost analysis, optimization identification
Output: Cost assessment, efficiency recommendations

Assessment Categories

Category	Key Areas
Architecture	Stack choices, patterns, technical debt
Infrastructure	Cloud, scaling, DR, monitoring
Security	Auth, encryption, vulnerabilities, compliance
Performance	Response times, throughput, optimization
DevOps	CI/CD, deployment, testing, monitoring

Integration Points

Technical Due Diligence: Core skill for tech DD
Code Quality Analyzer: Detailed code-level analysis
IP Patent Analyzer: Coordinate IP and tech review
Technical Assessor (Agent): Support DD agent

Technology Checklist

Frontend frameworks and mobile platforms
Backend languages and frameworks
Databases and data storage
Cloud infrastructure and services
Third-party integrations and dependencies
Development and deployment tools
Monitoring and observability

Best Practices

Request architecture documentation upfront
Supplement automated scanning with interviews
Focus on scalability relative to growth plans
Assess technical debt pragmatically
Consider technology choices in industry context