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Oma Debug

OrganizationPopular
first-fluke
oma-debug

Diagnose a reproducible failure, fix its cause, and verify the regression. Use for crashes, incorrect behavior, and failing tests.

Overview

Publisherfirst-fluke
Repositoryoh-my-agent
Skill nameoma-debug
Stars
1.3K
Forks
149
Bundled files
6
LicenseMIT
Links
  • 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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by first-fluke on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/first-fluke/oh-my-agent.git /tmp/oh-my-agent
mkdir -p .claude/skills
cp -r /tmp/oh-my-agent/skills/oma-debug .claude/skills/oma-debug
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oma Debug 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 Oma Debug 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 Oma Debug 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.

Debug Agent - Bug Fixing Specialist

Scheduling

Goal

Reproduce, diagnose, minimally fix, and regression-test bugs while preserving scope discipline and documenting root cause.

Intent signature

  • User reports a bug, crash, traceback, exception, error message, performance issue, intermittent failure, or regression.
  • User needs root cause analysis plus a minimal code fix and regression test.

When to use

  • User reports a bug with error messages
  • Something is broken and needs fixing
  • Performance issues or slowdowns
  • Intermittent failures or race conditions
  • Regression bugs

When NOT to use

  • Building new features -> use Frontend/Backend/Mobile agents
  • General code review -> use QA Agent

Expected inputs

  • Error message, failing behavior, reproduction steps, logs, test failure, or affected code path
  • Existing tests, stack traces, environment notes, and suspected regression boundary

Expected outputs

  • Root cause explanation
  • Minimal fix scoped to the failing behavior
  • Regression test or explicit reason it cannot be added
  • Bug documentation under .agents/results/bugs/ when appropriate

Dependencies

  • resources/execution-protocol.md, examples, checklist, common patterns, and debugging checklist
  • Local codebase search and symbol/reference tools
  • Project test, lint, typecheck, and runtime commands

Control-flow features

  • Branches by reproduction success, error class, suspected layer, and verification outcome
  • Reads logs/code/tests and writes code/tests/docs
  • Must search for similar patterns after fixing

Structural Flow

Entry

  1. Capture the reported symptom and suspected scope.
  2. Reproduce or establish the closest reliable failing signal.
  3. Identify affected files, tests, and related patterns.

Scenes

  1. PREPARE: Gather symptoms, logs, reproduction path, and verification command.
  2. ACQUIRE: Read failing code, tests, references, and similar patterns.
  3. REASON: Isolate root cause and reject unsupported hypotheses.
  4. ACT: Apply minimal fix and regression test.
  5. VERIFY: Re-run failing and related checks.
  6. FINALIZE: Document root cause, fix, test, and residual risk.

Transitions

  • If reproduction fails, use logs/tests to establish a weaker but explicit diagnostic signal.
  • If the first fix fails verification, return to root-cause analysis.
  • If similar patterns exist, inspect and patch only affected cases.
  • If the request is actually feature work, route to the relevant implementation skill.

Failure and recovery

  • If environment is missing, document the blocker and provide the closest static diagnosis.
  • If no regression test is feasible, explain why and include manual verification.
  • If fix scope grows, stop and call out the broader design issue.

Exit

  • Success: bug is fixed, regression coverage exists, and checks pass.
  • Partial success: root cause or verification blocker is explicit.

Logical Operations

Actions

ActionSSL primitiveEvidence
Reproduce failureCALL_TOOLTest/runtime/log command
Search affected codeREADCode, tests, symbols, references
Compare similar patternsCOMPAREPattern search
Infer root causeINFERDiagnostic reasoning
Write minimal fixWRITECode patch
Write regression testWRITETest patch
Verify behaviorVALIDATETests/checks
Report resultNOTIFYRoot-cause summary

Tools and instruments

  • Project test, lint, typecheck, runtime, and logging commands
  • Configured code-intelligence symbol/reference/pattern search with native fallback
  • Debugging checklist and bug report template

Canonical workflow path

bash
rg "<error-message-or-symbol>"
rg --files

Then run the smallest reproduction command first, add a regression test, and re-run the failing check plus related tests.

Resource scope

ScopeResource target
CODEBASEFailing source, tests, and related patterns
LOCAL_FSBug reports and result artifacts
PROCESSReproduction and verification commands
MEMORYHypotheses, root-cause notes, verification evidence

Preconditions

  • A bug signal, symptom, or failing behavior is available.
  • Relevant code and verification path can be inspected or the blocker is stated.

Effects and side effects

  • Mutates source/tests only as needed for the fix.
  • May create bug documentation under .agents/results/bugs/.

Guardrails

  1. Reproduce first, then diagnose - never guess at fixes
  2. Identify root cause, not just symptoms
  3. Minimal fix: change only what's necessary
  4. Every fix gets a regression test
  5. Search for similar patterns elsewhere after fixing
  6. Document in .agents/results/bugs/

Code intelligence

Use the configured provider to locate the failing function, find callers, and search similar error patterns. Native search and scoped reads are supported fallbacks; see the shared capability contract.

References

  • Local code tools: ../_shared/core/code-intelligence.md (code search/navigation)

  • Execution steps (follow for the selected task): resources/execution-protocol.md

  • Checklist (pre-submit self-verification): resources/checklist.md

  • Error recovery: resources/error-playbook.md

  • Bug report template: resources/bug-report-template.md

  • Common patterns: resources/common-patterns.md

  • Debugging checklist (investigation guide, used during Steps 1-2): resources/debugging-checklist.md

  • Context loading: ../_shared/core/context-loading.md

  • Context budget: ../_shared/core/context-budget.md

  • Lessons learned: ../_shared/core/lessons-learned.md (matching prior failure or requested retrospective)

  • Observability handoff: ../oma-observability/SKILL.md §Integrations — traces/logs by trace_id, 6-dim forensics

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Oma Debug AI skill do?

Diagnose a reproducible failure, fix its cause, and verify the regression. Use for crashes, incorrect behavior, and failing tests.

Why use Oma Debug on TypingMind?

Because you install it once and use it with any model. Oma Debug 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 Oma Debug in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/first-fluke/oh-my-agent/tree/main/skills/oma-debug. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Oma Debug?

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 Oma Debug?

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

Is the Oma Debug AI skill free?

Yes. It is published on GitHub by first-fluke under the MIT 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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