From coding-debugger
Use when the user asks to "add logging", "add tracing", "improve observability", "OpenTelemetry", "structured logging", or reports silent failures or no runtime visibility. Generates stack-appropriate logging with optional OTel.
How this skill is triggered — by the user, by Claude, or both
Slash command
/coding-debugger:logging-tracerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generate structured logging and tracing code tailored to the project's stack. Follow a tiered approach: start with zero dependencies, escalate only when the user needs distributed tracing.
Generate structured logging and tracing code tailored to the project's stack. Follow a tiered approach: start with zero dependencies, escalate only when the user needs distributed tracing.
Before generating code, detect the project's stack and existing logging:
package.json (Node.js/TypeScript), requirements.txt/pyproject.toml (Python), go.mod (Go), Cargo.toml (Rust), Gemfile (Ruby)If existing logging exists, extend it rather than replacing it. If uncertain about the stack, ask the user before generating code.
Generate a single logger module using only built-in language features. Output structured JSON to stderr (not stdout, which may be used for data or protocols).
Key requirements:
Refer to references/stack-templates.md for full implementation templates per language.
When the user needs persistent logs or the debugger's read_logs tool should discover them:
logs/app.jsonl in the project root (JSONL format, append-only)ts (Unix ms), level, msg, op (operation name)read_logs MCP toolWhen the user explicitly requests distributed tracing or mentions OTel/Jaeger/SigNoz:
Guide the user on strategic placement. Log at these points:
Avoid logging:
When the user has logs but needs help interpreting them, follow this diagnostic sequence:
Refer to references/log-analysis.md for common error signatures and diagnostic checklists.
Generated logging code integrates with the debugger's read_logs MCP tool when:
logs/, *.log, *.jsonl in project root)ts, level, msg)error.name, error.message, error.stack)After adding logging, tell the user they can read logs using:
Use the debugger read_logs tool with source "project" to view these logs.
When generating logging code:
Guides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.
npx claudepluginhub tyroneross/claude-code-debugger --plugin claude-code-debugger