debug

Diagnose training performance problems and systemic errors in AI deployment pipelines.

Updated Apr 13, 2026

Search Tags:#performance #debugging #profiling #async #error analysis #GIL

Ready to run

npx skills add https://github.com/Jiachen-T-Wang/tinker-swe --skill debug-jiachen-t-wang

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: debug
Source: https://github.com/Jiachen-T-Wang/tinker-swe/tree/main/skills/debug
Command: npx skills add https://github.com/Jiachen-T-Wang/tinker-swe --skill debug-jiachen-t-wang

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps users identify and troubleshoot training slowdowns, hanging sessions, output mismatches, error messages, and deployment problems by providing structured debugging procedures.

Core Features & Use Cases

Performance Diagnosis: Detects bottlenecks in training speed, including GIL contention and network delays.
Error Interpretation: Maps opaque SDK and system errors to root causes, guiding effective fixes.
Deep Profiling: Offers advanced debugging tools like async task dumps and stack monitoring for hanging sessions.
Use Case: When training is unexpectedly slow or hangs, use this Skill to pinpoint whether dependency issues, code blocking, or server outages are the cause.

Quick Start

Use the debug skill to collect live thread stacks and asyncio task statuses during a training run to identify blocking operations or resource contention.

Frequently Asked Questions about debug

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I diagnose training slowdowns caused by GIL contention?▼

Diagnose training slowdowns by collecting live thread stacks to pinpoint GIL contention and blocking operations. This Skill provides structured procedures to identify resource bottlenecks and guide effective fixes.

What is the best way to debug hanging sessions during an AI deployment?▼

Debug hanging sessions by utilizing advanced profiling tools like async task dumps and stack monitoring. This method captures asyncio task statuses during runs to identify code blocking or network delays.

How do I map opaque SDK error messages to root causes?▼

Map opaque SDK errors to root causes by applying structured error interpretation procedures. This Skill helps troubleshoot output mismatches and system errors, guiding effective fixes for deployment problems.

Can I use async task dumps to identify blocking operations in my training pipeline?▼

Yes, you can use async task dumps to identify blocking operations in your training pipeline. This Skill offers deep profiling capabilities to collect asyncio task statuses and diagnose dependency issues or resource contention.

Why does my training run hang and how can stack monitoring help?▼

Training runs hang due to code blocking, dependency issues, or server outages, which stack monitoring helps identify. By capturing live thread stacks, you can isolate the exact blocking operation causing the hang.