logging-patterns

Name: logging-patterns
Author: decebals

686stars133forks

How to install logging-patterns?

decebals/claude-code-java/logging-patterns

$npx -y skills add decebals/claude-code-java --skill logging-patterns

Installs into the current project.

Summary

Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.

Files · 1

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SKILL.md

1	# Logging Patterns Skill
2
3	Effective logging for Java applications with focus on structured, AI-parsable formats.
4
5	## When to Use
6	- User says "add logging" / "improve logs" / "debug this"
7	- Analyzing application flow from logs
8	- Setting up structured logging (JSON)
9	- Request tracing with correlation IDs
10	- AI/Claude Code needs to analyze application behavior
11
12	---
13
14	## AI-Friendly Logging
15
16	> Key insight: JSON logs are better for AI analysis - faster parsing, fewer tokens, direct field access.
17
18	### Why JSON for AI/Claude Code?
19
20	```
21	# Text format - AI must "interpret" the string
22	2026-01-29 10:15:30 INFO OrderService - Order 12345 created for user-789, total: 99.99
23
24	# JSON format - AI extracts fields directly
25	{"timestamp":"2026-01-29T10:15:30Z","level":"INFO","orderId":12345,"userId":"user-789","total":99.99}
26	```
27
28	\| Aspect \| Text \| JSON \|
29	\|--------\|------\|------\|
30	\| Parsing \| Regex/interpretation \| Direct field access \|
31	\| Token usage \| Higher (repeated patterns) \| Lower (structured) \|
32	\| Error extraction \| Parse stack trace text \| `exception` field \|
33	\| Filtering \| grep patterns \| `jq` queries \|
34
35	### Recommended Setup for AI-Assisted Development
36
37	```yaml
38	# application.yml - JSON by default
39	logging:
40	structured:
41	format:
42	console: logstash # Spring Boot 3.4+
43
44	# When YOU need to read logs manually:
45	# Option 1: Use jq
46	# tail -f app.log \| jq .
47
48	# Option 2: Switch profile temporarily
49	# java -jar app.jar --spring.profiles.active=human-logs
50	```
51
52	### Log Format Optimized for AI Analysis
53
54	```json
55	{
56	"timestamp": "2026-01-29T10:15:30.123Z",
57	"level": "INFO",
58	"logger": "com.example.OrderService",
59	"message": "Order created",
60	"requestId": "req-abc123",
61	"traceId": "trace-xyz",
62	"orderId": 12345,
63	"userId": "user-789",
64	"duration_ms": 45,
65	"step": "payment_completed"
66	}
67	```
68
69	Key fields for AI debugging:
70	- `requestId` - group all logs from same request
71	- `step` - track progress through flow
72	- `duration_ms` - identify slow operations
73	- `level` - quick filter for errors
74
75	### Reading Logs with AI/Claude Code
76
77	When asking AI to analyze logs:
78
79	```bash
80	# Get recent errors
81	cat app.log \| jq 'select(.level == "ERROR")' \| tail -20
82
83	# Follow specific request
84	cat app.log \| jq 'select(.requestId == "req-abc123")'
85
86	# Find slow operations
87	cat app.log \| jq 'select(.duration_ms > 1000)'
88	```
89
90	AI can then:
91	1. Parse JSON directly (no guessing)
92	2. Follow request flow via requestId
93	3. Identify exactly where errors occurred
94	4. Measure timing between steps
95
96	---
97
98	## Quick Setup (Spring Boot 3.4+)
99
100	### Native Structured Logging
101
102	Spring Boot 3.4+ has built-in support - no extra dependencies!
103
104	```yaml
105	# application.yml
106	logging:
107	structured:
108	format:
109	console: logstash # or "ecs" for Elastic Common Schema
110
111	# Supported formats: logstash, ecs, gelf
112	```
113
114	### Profile-Based Switching
115
116	```yaml
117	# application.yml (default - JSON for AI/prod)
118	spring:
119	profiles:
120	default: json-logs
121
122	---
123	spring:
124	config:
125	activate:
126	on-profile: json-logs
127	logging:
128	structured:
129	format:
130	console: logstash
131
132	---
133	spring:
134	config:
135	activate:
136	on-profile: human-logs
137	# No structured format = human-readable default
138	logging:
139	pattern:
140	console: "%d{HH:mm:ss.SSS} %-5level [%thread] %logger{36} - %msg%n"
141	```
142
143	Usage:
144	```bash
145	# Default: JSON (for AI, CI/CD, production)
146	./mvnw spring-boot:run
147
148	# Human-readable when needed
149	./mvnw spring-boot:run -Dspring.profiles.active=human-logs
150	```
151
152	---
153
154	## Setup for Spring Boot < 3.4
155
156	### Logstash Logback Encoder
157
158	pom.xml:
159	```xml
160	<dependency>
161	<groupId>net.logstash.logback</groupId>
162	<artifactId>logstash-logback-encoder</artifactId>
163	<version>7.4</version>
164	</dependency>
165	```
166
167	logback-spring.xml:
168	```xml
169	<?xml version="1.0" encoding="UTF-8"?>
170	<configuration>
171
172	<!-- JSON (default) -->
173	<springProfile name="!human-logs">
174	<appender name="JSON" class="ch.qos.logback.core.ConsoleAppender">
175	<encoder class="net.logstash.logback.encoder.LogstashEncoder">
176	<includeMdcKeyName>requestId</includeMdcKeyName>
177	<includeMdcKeyName>userId</includeMdcKeyName>
178	</encoder>
179	</appender>
180	<root level="INFO">
181	<appender-ref ref="JSON"/>
182	</root>
183	</springProfile>
184
185	<!-- Human-readable (optional) -->
186	<springProfile name="human-logs">
187	<appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
188	<encoder>
189	<pattern>%d{HH:mm:ss.SSS} %-5level [%thread] %logger{36} - %msg%n</pattern>
190	</encoder>
191	</appender>
192	<root level="INFO">
193	<appender-ref ref="CONSOLE"/>
194	</root>
195	</springProfile>
196
197	</configuration>
198	```
199
200	### Adding Custom Fie

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Type

logging-patterns

686stars133forks

View on GitHub

How to install logging-patterns?

decebals/claude-code-java/logging-patterns

$npx -y skills add decebals/claude-code-java --skill logging-patterns

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Logging Patterns Skill
2
3	Effective logging for Java applications with focus on structured, AI-parsable formats.
4
5	## When to Use
6	- User says "add logging" / "improve logs" / "debug this"
7	- Analyzing application flow from logs
8	- Setting up structured logging (JSON)
9	- Request tracing with correlation IDs
10	- AI/Claude Code needs to analyze application behavior
11
12	---
13
14	## AI-Friendly Logging
15
16	> Key insight: JSON logs are better for AI analysis - faster parsing, fewer tokens, direct field access.
17
18	### Why JSON for AI/Claude Code?
19
20	```
21	# Text format - AI must "interpret" the string
22	2026-01-29 10:15:30 INFO OrderService - Order 12345 created for user-789, total: 99.99
23
24	# JSON format - AI extracts fields directly
25	{"timestamp":"2026-01-29T10:15:30Z","level":"INFO","orderId":12345,"userId":"user-789","total":99.99}
26	```
27
28	\| Aspect \| Text \| JSON \|
29	\|--------\|------\|------\|
30	\| Parsing \| Regex/interpretation \| Direct field access \|
31	\| Token usage \| Higher (repeated patterns) \| Lower (structured) \|
32	\| Error extraction \| Parse stack trace text \| `exception` field \|
33	\| Filtering \| grep patterns \| `jq` queries \|
34
35	### Recommended Setup for AI-Assisted Development
36
37	```yaml
38	# application.yml - JSON by default
39	logging:
40	structured:
41	format:
42	console: logstash # Spring Boot 3.4+
43
44	# When YOU need to read logs manually:
45	# Option 1: Use jq
46	# tail -f app.log \| jq .
47
48	# Option 2: Switch profile temporarily
49	# java -jar app.jar --spring.profiles.active=human-logs
50	```
51
52	### Log Format Optimized for AI Analysis
53
54	```json
55	{
56	"timestamp": "2026-01-29T10:15:30.123Z",
57	"level": "INFO",
58	"logger": "com.example.OrderService",
59	"message": "Order created",
60	"requestId": "req-abc123",
61	"traceId": "trace-xyz",
62	"orderId": 12345,
63	"userId": "user-789",
64	"duration_ms": 45,
65	"step": "payment_completed"
66	}
67	```
68
69	Key fields for AI debugging:
70	- `requestId` - group all logs from same request
71	- `step` - track progress through flow
72	- `duration_ms` - identify slow operations
73	- `level` - quick filter for errors
74
75	### Reading Logs with AI/Claude Code
76
77	When asking AI to analyze logs:
78
79	```bash
80	# Get recent errors
81	cat app.log \| jq 'select(.level == "ERROR")' \| tail -20
82
83	# Follow specific request
84	cat app.log \| jq 'select(.requestId == "req-abc123")'
85
86	# Find slow operations
87	cat app.log \| jq 'select(.duration_ms > 1000)'
88	```
89
90	AI can then:
91	1. Parse JSON directly (no guessing)
92	2. Follow request flow via requestId
93	3. Identify exactly where errors occurred
94	4. Measure timing between steps
95
96	---
97
98	## Quick Setup (Spring Boot 3.4+)
99
100	### Native Structured Logging
101
102	Spring Boot 3.4+ has built-in support - no extra dependencies!
103
104	```yaml
105	# application.yml
106	logging:
107	structured:
108	format:
109	console: logstash # or "ecs" for Elastic Common Schema
110
111	# Supported formats: logstash, ecs, gelf
112	```
113
114	### Profile-Based Switching
115
116	```yaml
117	# application.yml (default - JSON for AI/prod)
118	spring:
119	profiles:
120	default: json-logs
121
122	---
123	spring:
124	config:
125	activate:
126	on-profile: json-logs
127	logging:
128	structured:
129	format:
130	console: logstash
131
132	---
133	spring:
134	config:
135	activate:
136	on-profile: human-logs
137	# No structured format = human-readable default
138	logging:
139	pattern:
140	console: "%d{HH:mm:ss.SSS} %-5level [%thread] %logger{36} - %msg%n"
141	```
142
143	Usage:
144	```bash
145	# Default: JSON (for AI, CI/CD, production)
146	./mvnw spring-boot:run
147
148	# Human-readable when needed
149	./mvnw spring-boot:run -Dspring.profiles.active=human-logs
150	```
151
152	---
153
154	## Setup for Spring Boot < 3.4
155
156	### Logstash Logback Encoder
157
158	pom.xml:
159	```xml
160	<dependency>
161	<groupId>net.logstash.logback</groupId>
162	<artifactId>logstash-logback-encoder</artifactId>
163	<version>7.4</version>
164	</dependency>
165	```
166
167	logback-spring.xml:
168	```xml
169	<?xml version="1.0" encoding="UTF-8"?>
170	<configuration>
171
172	<!-- JSON (default) -->
173	<springProfile name="!human-logs">
174	<appender name="JSON" class="ch.qos.logback.core.ConsoleAppender">
175	<encoder class="net.logstash.logback.encoder.LogstashEncoder">
176	<includeMdcKeyName>requestId</includeMdcKeyName>
177	<includeMdcKeyName>userId</includeMdcKeyName>
178	</encoder>
179	</appender>
180	<root level="INFO">
181	<appender-ref ref="JSON"/>
182	</root>
183	</springProfile>
184
185	<!-- Human-readable (optional) -->
186	<springProfile name="human-logs">
187	<appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
188	<encoder>
189	<pattern>%d{HH:mm:ss.SSS} %-5level [%thread] %logger{36} - %msg%n</pattern>
190	</encoder>
191	</appender>
192	<root level="INFO">
193	<appender-ref ref="CONSOLE"/>
194	</root>
195	</springProfile>
196
197	</configuration>
198	```
199
200	### Adding Custom Fie

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