Skip to content
cccskills
FreePublished on GitHub

Defense-in-Depth Validation

Validate at every layer data passes through to make bugs impossible

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md3.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

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

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

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

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

Don't stop at one validation point. Add checks at every layer.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

2D game development principles. Sprites, tilemaps, physics, camera.

The English summary is being prepared. Showing the original description.

VoDaiLocz/kilo-kit-mcp28Updated Sep 13, 2026

3D game development principles. Rendering, shaders, physics, cameras.

The English summary is being prepared. Showing the original description.

VoDaiLocz/kilo-kit-mcp28Updated Sep 13, 2026

Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

The English summary is being prepared. Showing the original description.

VoDaiLocz/kilo-kit-mcp28Updated Sep 13, 2026

Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.

The English summary is being prepared. Showing the original description.

VoDaiLocz/kilo-kit-mcp28Updated Sep 13, 2026

Use when monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.

The English summary is being prepared. Showing the original description.

VoDaiLocz/kilo-kit-mcp28Updated Sep 13, 2026

Use when building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.

The English summary is being prepared. Showing the original description.

VoDaiLocz/kilo-kit-mcp28Updated Sep 13, 2026

See all skills by VoDaiLocz

Report a problem with this skill