defense-in-depth

Enforce multi-layer data validation across API, service, test, and production scenarios.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/chriscarterux/chris-claude-stack --skill defense-in-depth-chriscarterux
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: defense-in-depth
Source: https://github.com/chriscarterux/chris-claude-stack/tree/main/skills/defense-in-depth
Command: npx skills add https://github.com/chriscarterux/chris-claude-stack --skill defense-in-depth-chriscarterux

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates recurring software bugs caused by invalid data by implementing validation at every layer of your system, preventing issues from slipping through single-point checks.

Core Features & Use Cases

  • Multi-Layer Validation: Automatically validates data at entry points, business logic, environment contexts, and debug layers.
  • Bug Prevention: Transforms your codebase from "we fixed the bug" to "we made the bug impossible".
  • Use Case: When your team encounters a bug where empty project directories cause git operations in wrong locations, this Skill guides implementing four validation layers that catch all edge cases and prevent recurrence.

Quick Start

I'm getting a bug where invalid data causes failures deep in my application. Help me implement defense-in-depth validation by identifying all data flow layers and adding appropriate checks at each point.

Frequently Asked Questions about defense-in-depth

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent bugs from invalid data passing through my application layers?▼

Defense-in-depth validation prevents bugs caused by invalid data by enforcing checks at multiple layers—API entry points, business logic, environment guards, and debug instrumentation—so invalid data cannot slip through single-point checks. Each layer validates independently with explicit error handling and consistent stack traces.

What validation layers should I implement to catch data errors early?▼

Implement four distinct validation layers: entry validation at API boundaries to reject malformed input, business logic validation to enforce state invariants, environment guards to verify runtime context, and debug instrumentation to surface diagnostics. Each layer requires explicit checks, consistent error handling, and test coverage.

When should I use multi-layer validation instead of checking data once?▼

Multi-layer validation is essential when bugs recur despite fixes, when data flows through multiple system boundaries, or when invalid state deep in your application causes failures. Single-point checks miss edge cases; layered validation makes bugs structurally impossible by catching errors at every stage data enters or transitions.

How do I implement defense-in-depth for APIs and services?▼

Define validation at API entry to reject invalid requests, add business logic checks before state changes, implement environment guards for context-specific rules, and add debug instrumentation for diagnostics. Document checks explicitly, use consistent error responses, and cover each layer with tests to ensure no invalid data reaches production logic.

What's the difference between entry validation and business logic validation?▼

Entry validation rejects malformed or missing data at API boundaries before processing begins. Business logic validation enforces domain rules and state invariants after entry—checking that operations are valid in context. Both are required; entry validation stops obvious errors, business logic validation prevents subtle bugs from valid-but-inappropriate data.

Do I need separate test coverage for each validation layer?▼

Yes. Each validation layer requires explicit test coverage to verify it catches invalid data and handles errors consistently. Test entry validation with malformed inputs, business logic validation with edge cases, environment guards with mismatched contexts, and debug instrumentation with diagnostics scenarios to ensure no layer leaks invalid data.