log-design

log-design is a skill for Claude Code, Codex from Crearize/ai-dev-helm. It costs 58 tokens per session (2,931 once invoked), scanned A, original, MIT.

A log-design review that checks application logs against common practices and Japanese legal requirements, including rules for electronic records and personal information.

In plain words
What is it for?
Use it to inspect log settings and existing log output, check what data is recorded, suggest implementation patterns, and produce a report.
Why use it?
It helps find missing log details, unsuitable log levels, and possible legal issues before they cause problems.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/crearize/ai-dev-helm/log-design
Any agent
npx skills add Crearize/ai-dev-helm --skill log-design
Clone the repo
git clone --depth 1 https://github.com/Crearize/ai-dev-helm

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 log-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/crearize/ai-dev-helm/log-design.svg)](https://agentmods.dev/skills/crearize/ai-dev-helm/log-design)
Your own site
<a href="https://agentmods.dev/skills/crearize/ai-dev-helm/log-design"><img src="https://agentmods.dev/badge/skills/crearize/ai-dev-helm/log-design.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,931 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00058 $0.02931
Opus 5 $0.00029 $0.01465
Sonnet 5 $0.00012 $0.00586
Haiku 4.5 $0.00006 $0.00293

Measured 3d ago against content hash 12c150e5fd6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

log-design 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 3d 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/project/log-design/SKILL.md · 301 lines

How it starts

The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Log Design Check - ログ設計チェック

プロジェクトのログ設計が一般的な基準と法的要件を満たしているか体系的にチェックし、不足があれば実装パターンを提示する。

参照: セキュリティ関連のログルールは documents/development/coding-rules/common-rules.md Section 4 も併せて確認すること。

実行フロー

Step 1: 現状分析(既存のログ設定・出力を確認)
  ↓
Step 2: 一般的ログ基準チェック
  ↓
Step 3: 法的要件チェック
  ↓
Step 4: 不足箇所の実装パターン提示
  ↓
Step 5: レポート出力

Step 1: 現状分析

以下を確認する:

  • ログライブラリ・設定ファイル(logback-spring.xml、pino設定等)
  • 既存のログ出力箇所
  • 取り扱うデータの種類(取引データ、個人情報、メール送信等)

Step 2: 一般的ログ基準チェック

ログレベル基準

レベル 用途
ERROR システム異常、復旧不可能なエラー DB接続失敗、外部API障害、未処理例外
WARN 想定内だが注意が必要な事象 リトライ発生、閾値超過、非推奨API使用
INFO ビジネス上重要なイベント ユーザーログイン/ログアウト、決済完了、重要な状態遷移
DEBUG 開発・調査用の詳細情報 リクエスト/レスポンス詳細、SQL実行詳細(本番では無効化)

構造化ログ実装パターン

Spring Boot + Logback (JSON形式):

// logback-spring.xml で net.logstash.logback.encoder.LogstashEncoder を使用
// または logback-spring.xml で JSON パターンを定義

// 出力例:
// {
//   "timestamp": "2025-01-08T10:00:00.000+09:00",
//   "level": "INFO",
//   "logger": "com.example.service.PaymentService",
//   "message": "Payment completed",
//   "traceId": "abc123",
//   "userId": "user-001",
//   "action": "PAYMENT_COMPLETE",
//   "amount": 10000,
//   "paymentId": "pay-001"
// }

@Slf4j
@Service
public class PaymentService {
    public void completePayment(Payment payment) {
        // MDC にトレース情報をセット
        MDC.put("action", "PAYMENT_COMPLETE");
        MDC.put("paymentId", payment.getId().toString());
        log.info("Payment completed: amount={}", payment.getAmount());
        MDC.clear();
    }
}

Next.js (API Routes / Server Actions):

// lib/logger.ts - 構造化ログユーティリティ
import pino from 'pino';

export const logger = pino({
  level: process.env.LOG_LEVEL || 'info',
  formatters: {
    level: (label) => ({ level: label }),
  },
  timestamp: pino.stdTimeFunctions.isoTime,
});

// 使用例: API Route
export async function POST(request: Request) {
  const body = await request.json();
  logger.info(
    { action: 'ORDER_CREATED', orderId: body.id, userId: session.userId },
    'Order created'
  );
}

Read the full file on GitHub · 301 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. 3d ago First seen · 301 lines · 58 tokens per session scan A 12c150e5fd6f

Subscribe to this mod's changes

log-design is a skill published in the GitHub repository Crearize/ai-dev-helm (4 stars, last pushed 9d ago), licensed MIT. It adds 58 tokens to every session and 2,931 once invoked, about $0.0003 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 2026-08-31.

Related

Other skills, from other repositories

tooluniverse-drug-research

Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory…

mims-harvard/ToolUniverse · 71 tokens

x-scorecard

OpenSSF Scorecard for assessing open source project security. Check security best practices and compliance. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.

x-cmd/x-cmd · 57 tokens

memstack-business-gdpr

Use this skill when the user says 'GDPR', 'data protection', 'privacy compliance', 'DPA', 'DSAR', 'data subject request', 'cookie consent', 'privacy audit', 'CCPA', or asks 'do I need GDPR for this repo'. Scans the repository to detect what personal data is collected, classifies sensitivity, determines whether GDPR…

cwinvestments/memstack · 121 tokens

catalyst-center-readonly

Query Cisco Catalyst Center read-only — device inventory, site hierarchy, wireless, assurance health, compliance, software images, events. All 514 read-only API operations reachable through 8 grouped dispatchers. Use when asked what Catalyst Center manages, where a device sits, what its health or compliance state is…

automateyournetwork/netclaw · 78 tokens

build-audit-logs

Build or review audit trails in TypeScript/JavaScript apps using evlog (pipelines, typed actions, denials, retention, compliance-style reviews). For application code, not for extending the evlog package.

activepieces/activepieces · 49 tokens

nda-review

Use when the user uploads or pastes a non-disclosure agreement and asks for review, redline, risk assessment, or a recommendation on whether to sign. Identifies missing standard protections, one-sided or unusual provisions, and operational issues; produces a structured report with severity ratings and citations to…

LegalQuants/lq-ai · 79 tokens