defense-in-depth

defense-in-depth is a skill for Claude Code, Codex from event4u-app/agent-config. It costs 40 tokens per session (1,350 once invoked), scanned A, original, MIT.

A validation approach checks a value at each layer it passes through, including input, business logic, environment, and monitoring.

In plain words
What is it for?
It helps fix bugs involving bad input, protect new entry points and callers, and ensure tests or mocks do not skip safeguards.
Why use it?
It reduces the chance that invalid data bypasses one check and causes a failure deeper in the program or through another code path.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps fix bugs involving bad input, protect new entry points and callers, and ensure tests or mocks do not skip safeguards.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/event4u-app/agent-config/defense-in-depth
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add event4u-app/agent-config --skill defense-in-depth
Clone the repo
git clone --depth 1 https://github.com/event4u-app/agent-config

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for defense-in-depth

README.md
[![agentmods](https://agentmods.dev/badge/skills/event4u-app/agent-config/defense-in-depth/github.svg)](https://agentmods.dev/skills/event4u-app/agent-config/defense-in-depth)
Your own site
<a href="https://agentmods.dev/skills/event4u-app/agent-config/defense-in-depth"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/defense-in-depth/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for defense-in-depth

Your own site · 80×15
<a href="https://agentmods.dev/skills/event4u-app/agent-config/defense-in-depth"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/defense-in-depth.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,350 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Data Exfiltration · line 92
    Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.
    Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.01350
Opus 5 $0.00020 $0.00675
Sonnet 5 $0.00008 $0.00270
Haiku 4.5 $0.00004 $0.00135

Measured 7d ago against content hash d8bdc8e520d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

defense-in-depth scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

src/skills/defense-in-depth/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

defense-in-depth

Validate at every layer the value passes through. Fixing the bug at one layer is locally sufficient and globally fragile — the next refactor, code path, mock, or platform edge case will rediscover it. Four-layer validation makes the bug structurally impossible.

When to use

  • Bug fix where invalid data caused failure several frames deep.
  • New entry point that funnels external input into existing internals.
  • Refactor that adds a second caller to a previously single-caller routine.
  • Test setup that shortcuts production guards (mocks bypassing entry validation).

Do NOT use when:

  • Pure formatting / style change — no data flow, no layers to defend.
  • Boundary validation alone is correct (e.g. immutable value object with constructor invariant) — route to laravel-validation.
  • The fix belongs at a single architectural seam — adding three more guards is over-engineering. Use the gate function below to stop early.

Procedure: Apply the four-layer pattern

Step 0: Analyze the data flow before adding guards

  1. Identify where the bad value originates (test fixture, request body, env var, config).
  2. List every function that receives the value before the failure point.
  3. Mark which functions are reachable from production paths and which only from tests.

Step 1: Layer 1 — Entry-point validation

Reject obviously invalid input at the API / route / command boundary. In Laravel this is FormRequest rules; in Express a zod-validated middleware; in pure services it is the public method on the service.

public function createProject(string $name, string $workingDirectory): Project
{
    if (trim($workingDirectory) === '') {
        throw new InvalidArgumentException('workingDirectory cannot be empty');
    }
    if (! is_dir($workingDirectory)) {
        throw new InvalidArgumentException("workingDirectory does not exist: {$workingDirectory}");
    }
    if (! is_writable($workingDirectory)) {
        throw new InvalidArgumentException("workingDirectory is not writable: {$workingDirectory}");
    }
    // ... proceed
}

Read the full file on GitHub · 158 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 158 lines · 40 tokens per session scan A d8bdc8e520d6

Subscribe to this mod's changes

defense-in-depth is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,350 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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