piomin/claude-ai-spring-boot is a starter template for creating Spring Boot applications with Claude Code. Developers clone it as a structured foundation when using Claude Code to generate Spring Boot projects.
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.
npx skills add piomin/claude-ai-spring-boot --skill logging-patternsgit clone --depth 1 https://github.com/piomin/claude-ai-spring-bootWrote 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.
[](https://agentmods.dev/skills/piomin/claude-ai-spring-boot/logging-patterns)<a href="https://agentmods.dev/skills/piomin/claude-ai-spring-boot/logging-patterns"><img src="https://agentmods.dev/badge/skills/piomin/claude-ai-spring-boot/logging-patterns/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.
<a href="https://agentmods.dev/skills/piomin/claude-ai-spring-boot/logging-patterns"><img src="https://agentmods.dev/badge/skills/piomin/claude-ai-spring-boot/logging-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.02645 |
| Opus 5.5 | $0.00020 | $0.01058 |
| Sonnet 5.5 | $0.00010 | $0.00529 |
| Haiku 4.5 | $0.00005 | $0.00265 |
Grade A, and why
logging-patterns 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- logging-patterns — 88% identical, 341 lines differ
How it starts
The opening of the file, as written. The whole thing — 403 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logging Patterns Skill
Rule: JSON is the default log format. Plain text logging is only for local development with human-logs profile. Production, CI/CD, and Kubernetes environments must use structured JSON.
When to Use
- User says "add logging" / "improve logs" / "debug this"
- Analyzing application flow from logs
- Setting up structured logging (JSON)
- Request tracing with correlation IDs
- AI/Claude Code needs to analyze application behavior
AI-Friendly Logging
Key insight: JSON logs are better for AI analysis - faster parsing, fewer tokens, direct field access.
Why JSON for AI/Claude Code?
# Text format - AI must "interpret" the string
2026-01-29 10:15:30 INFO OrderService - Order 12345 created for user-789, total: 99.99
# JSON format - AI extracts fields directly
{"timestamp":"2026-01-29T10:15:30Z","level":"INFO","orderId":12345,"userId":"user-789","total":99.99}
| Aspect | Text | JSON |
|---|---|---|
| Parsing | Regex/interpretation | Direct field access |
| Token usage | Higher (repeated patterns) | Lower (structured) |
| Error extraction | Parse stack trace text | exception field |
| Filtering | grep patterns | jq queries |
Recommended Setup for AI-Assisted Development
# application.yml - JSON by default
logging:
structured:
format:
console: logstash # Spring Boot 4.x
# When YOU need to read logs manually:
# Option 1: Use jq
# tail -f app.log | jq .
# Option 2: Switch profile temporarily
# java -jar app.jar --spring.profiles.active=human-logs
Log Format Optimized for AI Analysis
{
"timestamp": "2026-01-29T10:15:30.123Z",
"level": "INFO",
"logger": "pl.piomin.services.OrderService",
"message": "Order created",
"requestId": "req-abc123",
"traceId": "trace-xyz",
"orderId": 12345,
"userId": "user-789",
"duration_ms": 45,
"step": "payment_completed"
}
Key fields for AI debugging:
requestId- group all logs from same requeststep- track progress through flowduration_ms- identify slow operationslevel- quick filter for errors
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.
- 6d ago Changed · +151 lines 68b619d46707
- 1mo ago First seen · 252 lines · 50 tokens per session scan A 3006e2266e77
logging-patterns is a skill published in the GitHub repository piomin/claude-ai-spring-boot (1,425 stars, last pushed yesterday), licensed Apache-2.0. It adds 50 tokens to every session and 2,645 once invoked, about $0.0002 per session on Opus 5.5. 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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