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safeguarding-ai-generated-code

safeguarding-ai-generated-code is a skill for Claude Code, Codex from DavidVujic/my-eca-config. It costs 32 tokens per session (403 once invoked), scanned A, original, MIT.

A quality-check workflow for AI-generated or AI-modified code, called a Code Health safeguard. It reviews changed files and change sets for maintainability problems and regression risk.

In plain words
What is it for?
Use it after changing code, before recommending a commit, or when checking whether staged, branch, or pull-request changes are ready.
Why use it?
It catches code-quality issues before a commit, handoff, or pull request makes the changes harder to maintain.

Skill for Claude CodeCodex

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

not rated 11repo 11d ago A scan 32 tokens original MIT

Good fit Use it after changing code, before recommending a commit, or when checking whether staged, branch, or pull-request changes are ready.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/davidvujic/my-eca-config/safeguarding-ai-generated-code
View source ↗ DavidVujic/my-eca-config
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 DavidVujic/my-eca-config --skill safeguarding-ai-generated-code
Clone the repo
git clone --depth 1 https://github.com/DavidVujic/my-eca-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 safeguarding-ai-generated-code

README.md
[![agentmods](https://agentmods.dev/badge/skills/davidvujic/my-eca-config/safeguarding-ai-generated-code.svg)](https://agentmods.dev/skills/davidvujic/my-eca-config/safeguarding-ai-generated-code)
Your own site
<a href="https://agentmods.dev/skills/davidvujic/my-eca-config/safeguarding-ai-generated-code"><img src="https://agentmods.dev/badge/skills/davidvujic/my-eca-config/safeguarding-ai-generated-code.svg" alt="Measured on agentmods" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 403 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.
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 $0.00032 $0.00403
Opus 5 $0.00016 $0.00201
Sonnet 5 $0.00006 $0.00081
Haiku 4.5 $0.00003 $0.00040

Measured 8d ago against content hash 66af86242a41, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

safeguarding-ai-generated-code 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 8d 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.

skills/safeguarding-ai-generated-code/SKILL.md · 41 lines

What it actually says

Safeguarding AI-Generated Code

Overview

Use Code Health safeguards before declaring AI-touched code ready. The goal is to catch maintainability regressions early and prevent agents from normalizing technical debt.

When to Use

  • The agent changed code and is about to suggest a commit.
  • The user asks whether a branch or staged changes are safe to merge.
  • The workflow needs a quality gate for AI-generated code.

Do not use this skill for broad refactoring discovery or project-level prioritization.

Quick Reference

  • code_health_review: Review each AI-modified file immediately after the change.
  • pre_commit_code_health_safeguard: Check staged or modified files before commit.
  • analyze_change_set: Check a branch or PR-style change set against a base ref.

Implementation

  1. After each AI modification to a file, run code_health_review on that file.
  2. If the review reports maintainability problems or regression risk, refactor the file in small steps and review it again.
  3. Run pre_commit_code_health_safeguard before commit-oriented recommendations as a broader gate across staged or modified files.
  4. Run analyze_change_set before PR-oriented recommendations as a final branch-level gate.
  5. If either later gate reports a regression, inspect the affected files with code_health_review and keep iterating until the issue is removed or the user explicitly accepts the risk.

Common Mistakes

  • Waiting until commit time to run the first Code Health check.
  • Treating safeguard output as optional guidance instead of a release gate.
  • Declaring work done after a failing safeguard.
  • Jumping straight to broad rewrites instead of inspecting the flagged files first.
  • Treating an accepted risk as invisible; call it out explicitly.
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. 8d ago First seen · 41 lines · 32 tokens per session scan A 66af86242a41

Subscribe to this mod's changes

safeguarding-ai-generated-code is a skill published in the GitHub repository DavidVujic/my-eca-config (11 stars, last pushed 11d ago), licensed MIT. It adds 32 tokens to every session and 403 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 2026-08-30.

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