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service-debugging

service-debugging

github.com/c0x12cDevelopment109112 installsUpdated 19w ago
Repository

About service-debugging

A structured service-debugging guide for developers, covering symptom collection through fix verification. It uses logs, deployment history, reproduction, and root-cause analysis to guide investigations.

Key features

  1. 01Gather symptoms and affected scope first
  2. 02Check deploy history, health, and logs
  3. 03Narrow investigations by error type
  4. 04Find causes through reproduction and git bisect
  5. 05Test the failure before fixing and verifying

Use cases

  1. 01Investigate API errors or service crashes
  2. 02Diagnose slow queries, timeouts, or missing data
  3. 03Trace regressions that appear after a deployment

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/c0x12c/ai-toolkit --skill service-debugging

After installing, type/service-debuggingin Claude Code to confirm it loaded.

Bundled filescommon-issues.md

Details

From the project README

Service Debugging

Structured approach to investigating and fixing service issues. Symptoms in, root cause out.

When to Use

  • API endpoint returning errors (4xx, 5xx)
  • Performance degradation or slow queries
  • Service not starting or crashing
  • Data inconsistency between services
  • After a deploy when something broke
  • User reports "something is broken"

Process

1. Gather Symptoms

Before touching code, collect:

  • What's broken? (specific endpoint, feature, or behavior)
  • When did it start? (after a deploy? gradually? suddenly?)
  • Who's affected? (all users, specific users, specific data?)
  • Error messages? (logs, HTTP responses, stack traces)
2. Check the Obvious

Run these first — they catch 80% of issues:

# Recent deploys (did someone push something?)
git log --oneline -10

# Service health
curl -s http://localhost:8080/health | jq .

# Recent errors in logs
grep -i "error\|exception\|fatal" logs/app.log | tail -20

# Database connectivity
psql -h $DB_HOST -U $DB_USER -d $DB_NAME -c "SELECT 1"

# Environment variables (missing or wrong?)
env | grep -i "DB_\|API_\|SECRET_" | sort
3. Narrow Down
SymptomCheck First
500 errorsStack trace in logs → find the throwing line
404 errorsRoute registration → is the controller loaded?
401/403 errorsAuth config → is @Secured correct? Token valid?
Slow responseDatabase → run EXPLAIN on the slow query
TimeoutExternal service → is the downstream API responding?
Data missingSoft delete → is deleted_at set? Wrong query filter?
Service won't startBean creation → check @Factory and @Singleton wiring
4. Reproduce
  • Can you trigger the bug locally?
  • What's the minimal request that fails?
  • Does it fail consistently or intermittently?
5. Find Root Cause

Use git bisect if it's a regression:

git bisect start
git bisect bad HEAD
git bisect good <last-known-good-commit>
# Test each commit until you find the one that broke it

Use grep to find related code:

# Find where the error message comes from
grep -r "error message text" --include="*.kt" src/

# Find all callers of a broken function
grep -r "functionName" --include="*.kt" src/
6. Fix and Verify
  1. Write a test that reproduces the bug (red)
  2. Fix the code (green)
  3. Run full test suite
  4. Test manually if it's a user-facing issue

See common-issues.md for a catalog of frequently seen bugs and their fixes.

Gotchas

  • Don't fix the symptom, fix the cause. Adding a null check that hides a data issue means the data issue will bite you later.
  • Check the deploy log before blaming the code. Config changes, environment variable updates, and infra changes cause more outages than code bugs.
  • "It works on my machine" usually means environment difference. Compare local env vars, database state, and service versions with the target environment.
  • Intermittent failures are usually race conditions. If it fails 1 in 10 times, look for concurrent access, shared mutable state, or connection pool exhaustion.
  • Don't restart the service as your first debugging step. You'll lose the state that helps you diagnose. Read logs first, then restart if needed.
  • Soft-deleted records are the #1 "data missing" cause. Always check deleted_at IS NULL in your queries.

Rules

  • Always gather symptoms before changing code
  • Write a failing test before fixing
  • Check recent git history — most bugs are regressions
  • Don't deploy a fix without understanding the root cause
  • Document the incident if it affected users

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