Debugging

Organization

ovh

debugging

Systematically diagnose and fix bugs using logs, stack traces, and targeted experiments

Overview

Publisher	ovh
Repository	`shai`
Skill name	`debugging`
Stars	627
Forks	60
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by ovh on GitHub. Read the source before you install it.

Installation

Install the Debugging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/ovh/shai/tree/main/shai-core/examples/skills/debugging
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ovh/shai.git /tmp/shai
mkdir -p .claude/skills
cp -r /tmp/shai/shai-core/examples/skills/debugging .claude/skills/debugging

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Debugging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Debugging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Debugging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Debugging

Purpose

Provide a structured approach to diagnosing and fixing bugs in the SHAI codebase.

Debugging Workflow

1. Reproduce the Issue

Identify the exact command or action that triggers the bug.
Note the expected vs. actual behavior.
Check if the issue is reproducible or intermittent.

2. Gather Information

Run with RUST_BACKTRACE=1 to get full stack traces.
Check logs for error messages or warnings.
Use git log --oneline -10 to see recent changes that might have introduced the bug.
Run git diff to check for uncommitted changes.

3. Isolate the Problem

Narrow down the failing component:

bash
# Run specific tests
cargo test -p shai-core -- <test_name>

# Run with backtrace
RUST_BACKTRACE=1 cargo test -p shai-core -- <test_name> -- --nocapture

Add temporary dbg!() or eprintln!() statements to trace execution flow.

Use cargo expand to debug macro-generated code:

bash
cargo expand -p shai-core --tests 2>/dev/null | less

4. Formulate and Test Hypotheses

State your hypothesis clearly: "The bug is caused by X because Y."
Write a minimal reproduction test case.
Fix the root cause, not just the symptom.
Verify the fix doesn't break other tests: cargo test.

5. Verify the Fix

Run the full test suite.
Test edge cases around the fix.
Check for similar patterns elsewhere in the codebase that might have the same bug.

Common Issues in This Project

Tool Registration Failures

Check shai-core/src/tools/mod.rs for proper module declarations and re-exports.
Verify the #[tool] macro is correctly applied.

MCP Connection Issues

Check the MCP configuration format.
Verify the MCP server is running and accessible.
Inspect the SSE/stdio transport layer for connection errors.

Prompt Template Errors

Check shai-core/src/runners/coder/prompt.rs for template variable mismatches.
Ensure all {{PLACEHOLDER}} variables are properly resolved.

Guidelines

Always start with reproduction — a bug you can't reproduce is one you can't fix.
Make minimal changes to fix the issue.
Add a regression test to prevent the bug from recurring.
Clean up any debug prints before committing.

Frequently asked questions

What does the Debugging AI skill do?

Systematically diagnose and fix bugs using logs, stack traces, and targeted experiments

Why use Debugging on TypingMind?

Because you install it once and use it with any model. Debugging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Debugging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ovh/shai/tree/main/shai-core/examples/skills/debugging. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Debugging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Debugging?

As many as you like. As long as a model supports skills, you can use Debugging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Debugging AI skill free?

Yes. It is published on GitHub by ovh under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Debugging

Purpose

Debugging Workflow

1. Reproduce the Issue

2. Gather Information

3. Isolate the Problem

4. Formulate and Test Hypotheses

5. Verify the Fix

Common Issues in This Project

Tool Registration Failures

MCP Connection Issues

Prompt Template Errors

Guidelines

Frequently asked questions

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