180-java-observability-logging

A guide to adding and checking logs in Java programs using common logging libraries such as SLF4J, Logback, and Log4j2. It covers log levels, configuration, security, and monitoring.

In plain words
What is it for?
Use it to choose a Java logging setup, write consistent messages, configure formats and log rotation, send logs to central systems, create alerts, and test logging behavior.
Why use it?
It helps developers produce useful logs without exposing passwords or personal data, while keeping output manageable across development and production.

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/jabrena/cursor-rules-examples/180-java-observability-logging
Any agent
npx skills add jabrena/cursor-rules-examples --skill 180-java-observability-logging
Clone the repo
git clone --depth 1 https://github.com/jabrena/cursor-rules-examples

Made for: Claude Code, Codex.

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 542 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 $0.00085 $0.00542
Opus 5 $0.00043 $0.00271
Sonnet 5 $0.00017 $0.00108
Haiku 4.5 $0.00009 $0.00054

Measured 2d ago against content hash 6b6e7b2216be, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

180-java-observability-logging 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 2d 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.

.agents/skills/180-java-observability-logging/SKILL.md · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Java Logging Best Practices

Implement effective Java logging following standardized frameworks, meaningful log levels, core practices (parameterized logging, exception handling, no sensitive data), flexible configuration, security-conscious logging, monitoring and alerting, and comprehensive logging validation through testing.

What is covered in this Skill?

  • Standardized framework selection: SLF4J facade with Logback or Log4j2
  • Meaningful and consistent log levels: ERROR, WARN, INFO, DEBUG, TRACE
  • Core practices: parameterized logging, proper exception handling, avoiding sensitive data
  • Configuration: environment-specific (logback.xml, log4j2.xml), output formats, log rotation
  • Security: mask sensitive data, control log access, secure transmission, GDPR/HIPAA compliance
  • Log monitoring and alerting: centralized aggregation (ELK, Splunk, Loki), automated alerts
  • Logging validation through testing: assert log messages, verify formats, test levels, measure performance impact

Scope: The reference is organized by examples (good/bad code patterns) for each core area. Apply recommendations based on applicable examples.

Constraints

Before applying any logging recommendations, ensure the project compiles. Compilation failure is a blocking condition. After applying improvements, run full verification.

  • MANDATORY: Run ./mvnw compile or mvn compile before applying any change
  • SAFETY: If compilation fails, stop immediately — do not proceed until resolved
  • VERIFY: Run ./mvnw clean verify or mvn clean verify after applying improvements
  • BEFORE APPLYING: Read the reference for detailed good/bad examples, constraints, and safeguards for each logging pattern

When to use this skill

  • Review Java code for logging and observability
  • Apply best practices for logging and observability in Java code

Reference

For detailed guidance, examples, and constraints, see references/180-java-observability-logging.md.

Read the full file on GitHub · 42 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 42 lines · 85 tokens per session scan A 6b6e7b2216be

Subscribe to this mod's changes

180-java-observability-logging is a skill published in the GitHub repository jabrena/cursor-rules-examples (2 stars, last pushed 6d ago), licensed Apache-2.0. It adds 85 tokens to every session and 542 once invoked, about $0.0004 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.

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