Does it support CLI and logging configuration?

Absolutely. It provides guidance on forcing JSON output, mapping standardized exit codes, and ensuring that log redaction and child logger contexts are correctly implemented.

What is the primary purpose of the Outfitter Stack Debugger?

It is designed to help developers troubleshoot issues within the Outfitter infrastructure, specifically focusing on Result types, MCP integration, and CLI logging consistency.

Can it help fix MCP tools that aren't appearing?

Yes, it verifies that tools are registered before the server starts and checks that schemas use valid Zod descriptions required for AI discovery.

How does this skill assist with TypeScript Result types?

It identifies common mistakes like missing awaits, reassigning variables that break type narrowing, and losing error context, providing 'GOOD' vs 'BAD' code patterns for correction.

Outfitter Stack Debugger

Name: Outfitter Stack Debugger
Author: outfitter-dev

byoutfitter-dev

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Analíticas y Monitorización

Troubleshoots and resolves technical issues within the Outfitter infrastructure, including Result handling, MCP integration, and CLI logging.

The Outfitter Stack Debugger is a specialized skill designed to diagnose and fix common pitfalls in Bun-first Outfitter projects. It provides expert guidance on handling Result types to prevent async errors and broken type narrowing, ensures Model Context Protocol (MCP) tools are correctly registered and invoked, and standardizes CLI output and exit codes. Whether you are dealing with failed log redactions, missing context in traces, or schema validation errors, this skill provides the patterns and diagnostic steps necessary to maintain a stable and observable stack.

Características Principales

01MCP tool registration and invocation troubleshooting

022 GitHub stars

03Log redaction and context hierarchy verification

04Result & Error handling pattern diagnostics

05Zod schema and TypeScript type narrowing validation

06CLI output mode and exit code standardization

Casos de Uso

01Fixing 'Result' objects that fail to narrow types or return unexpected 'err' states.

02Ensuring CLI tools properly output JSON and exit with the correct status codes for CI/CD.

03Debugging why an MCP tool is missing from the AI interface or failing during execution.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add outfitter-dev/outfitter debug

For use in Claude.ai and ChatGPT

Download Skill