defense-in-depth
Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossible
Best use case
defense-in-depth is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossible
Teams using defense-in-depth should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/defense-in-depth/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How defense-in-depth Compares
| Feature / Agent | defense-in-depth | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossible
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Defense-in-Depth Validation
## Overview
When you fix a bug caused by invalid data, adding validation at one place feels sufficient. But that single check can be bypassed by different code paths, refactoring, or mocks.
**Core principle:** Validate at EVERY layer data passes through. Make the bug structurally impossible.
## Why Multiple Layers
Single validation: "We fixed the bug"
Multiple layers: "We made the bug impossible"
Different layers catch different cases:
- Entry validation catches most bugs
- Business logic catches edge cases
- Environment guards prevent context-specific dangers
- Debug logging helps when other layers fail
## The Four Layers
### Layer 1: Entry Point Validation
**Purpose:** Reject obviously invalid input at API boundary
```typescript
function createProject(name: string, workingDirectory: string) {
if (!workingDirectory || workingDirectory.trim() === '') {
throw new Error('workingDirectory cannot be empty');
}
if (!existsSync(workingDirectory)) {
throw new Error(`workingDirectory does not exist: ${workingDirectory}`);
}
if (!statSync(workingDirectory).isDirectory()) {
throw new Error(`workingDirectory is not a directory: ${workingDirectory}`);
}
// ... proceed
}
```
### Layer 2: Business Logic Validation
**Purpose:** Ensure data makes sense for this operation
```typescript
function initializeWorkspace(projectDir: string, sessionId: string) {
if (!projectDir) {
throw new Error('projectDir required for workspace initialization');
}
// ... proceed
}
```
### Layer 3: Environment Guards
**Purpose:** Prevent dangerous operations in specific contexts
```typescript
async function gitInit(directory: string) {
// In tests, refuse git init outside temp directories
if (process.env.NODE_ENV === 'test') {
const normalized = normalize(resolve(directory));
const tmpDir = normalize(resolve(tmpdir()));
if (!normalized.startsWith(tmpDir)) {
throw new Error(
`Refusing git init outside temp dir during tests: ${directory}`
);
}
}
// ... proceed
}
```
### Layer 4: Debug Instrumentation
**Purpose:** Capture context for forensics
```typescript
async function gitInit(directory: string) {
const stack = new Error().stack;
logger.debug('About to git init', {
directory,
cwd: process.cwd(),
stack,
});
// ... proceed
}
```
## Applying the Pattern
When you find a bug:
1. **Trace the data flow** - Where does bad value originate? Where used?
2. **Map all checkpoints** - List every point data passes through
3. **Add validation at each layer** - Entry, business, environment, debug
4. **Test each layer** - Try to bypass layer 1, verify layer 2 catches it
## Example from Session
Bug: Empty `projectDir` caused `git init` in source code
**Data flow:**
1. Test setup → empty string
2. `Project.create(name, '')`
3. `WorkspaceManager.createWorkspace('')`
4. `git init` runs in `process.cwd()`
**Four layers added:**
- Layer 1: `Project.create()` validates not empty/exists/writable
- Layer 2: `WorkspaceManager` validates projectDir not empty
- Layer 3: `WorktreeManager` refuses git init outside tmpdir in tests
- Layer 4: Stack trace logging before git init
**Result:** All 1847 tests passed, bug impossible to reproduce
## Key Insight
All four layers were necessary. During testing, each layer caught bugs the others missed:
- Different code paths bypassed entry validation
- Mocks bypassed business logic checks
- Edge cases on different platforms needed environment guards
- Debug logging identified structural misuse
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