Implement structured logging for API requests with automatic correlation IDs, PII redaction, performance metrics, and security audit trails in JavaScript, Python, and Java backends. Use the setup command to configure request/response capture and log shipping in Node.js or Python apps for debugging, compliance, and observability workflows.
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Professional financial modeling toolkit for Claude Code with auto-invoked Skills and Excel MCP integration. Build DCF models, LBO analysis, variance reports, and pivot tables using natural language.
Claude Code skill pack for Flexport (24 skills)
Complete operations kit for FairDB PostgreSQL as a Service - VPS setup, PostgreSQL management, customer provisioning, monitoring, and backup automation
Claude Code skill pack for Klaviyo (24 skills)
Claude Code skill pack for Ramp (24 skills)
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin api-request-loggerAnalyze logs for performance insights and issues
Structured logging with proper levels, context, PII handling, centralized aggregation. Use for application logging, log management integration, distributed tracing, or encountering log bloat, PII exposure, missing context errors.
Backend platform discipline: observability, API design, and service architecture practices
Commands for setting up monitoring and observability
Observability hooks for Claude Code: comprehensive event logging, performance metrics, and session diagnostics. Provides full audit trail of all Claude Code interactions without modifying behavior.
Analyze Claude Code agent session transcripts to identify inefficiencies, anti-patterns, repeated mistakes, missing tooling opportunities, and user frustration signals for continuous improvement