Root Cause Finder

Organization

instructa

root-cause-finder

Performs root-cause-first debugging and review by tracing expected behavior to the first unintended side effect before changing contracts, parsing, or types. Use when debugging protocol errors, deserialization failures, null payloads, missing fields, restore or hydration issues, state-ownership bugs, unexpected requests, background mutations, or reviewing junior-created code where the visible failure may be downstream noise.

Overview

Publisher	instructa
Repository	`agent-skills`
Skill name	`root-cause-finder`
Stars	141
Forks	16
Bundled files	Instructions only
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 instructa on GitHub. Read the source before you install it.

Installation

Install the Root Cause Finder 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.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/instructa/agent-skills/tree/main/skills/engineering/root-cause-finder

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/instructa/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/engineering/root-cause-finder .claude/skills/root-cause-finder

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

Use it in TypingMind

Enable Root Cause Finder 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 Root Cause Finder 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 Root Cause Finder 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.

Root-Cause Finder

Core Instruction

Before fixing the error, prove whether the code path that produced it was intended.

Do not stop at the first contract, parsing, type, null, or schema error. Treat it as a possible symptom.

Default Workflow

State the expected behavior in plain language.
State the invariant in one sentence.
State what definitely did not happen.
Trace the causal chain from the intended action or system event to the observed system effect.
Ask whether the request or mutation should have happened at all.
Identify the canonical source of truth and every competing source.
Find the first unintended side effect or write.
Only then decide whether a downstream contract fix is still necessary.

Questions To Answer In Order

What user action or system event was supposed to happen?
What exact call path caused this request or response?
Should this request, mutation, or side effect have happened at all under the expected behavior and invariants?
Who owns the state at each layer?
Is there observer-driven syncing, lifecycle startup code, persistence restore, retry logic, background work, or multiple sources of truth causing an unintended side effect?
If a contract is violated, is the contract wrong, or did unintended logic reach the contract?

Rules

Do not make the contract more permissive unless you can prove the observed payload is intended in the final design.
Prefer fixing the upstream logic bug over accepting bad downstream data.
Separate symptom, trigger, root cause, minimal safe fix, and architectural follow-up.
If a low-level fix is still needed, explain why the upstream fix is not sufficient or why both are required.
Identify the correct layer to fix first.
Name the first visible wrong behavior, not only the final error.

Hidden Write Checks

Treat non-explicit writes as suspicious by default.

Audit lifecycle hooks, callbacks, subscribers, watchers, interceptors, middleware, retries, background jobs, cache refreshers, persistence restore, scheduled tasks, and startup code.
Check whether derived data is being mirrored into another store, cache, file, queue, session, or database through an observer or helper layer.
Prefer explicit command handlers, request handlers, job runners, or user actions as writers; treat startup-time and background writes as suspects until proven intentional.
If a framework has automatic reactivity or lifecycle execution, map this rule onto its equivalent constructs without assuming the framework behavior is correct.

Output Format

Use this structure:

Expected behavior
Invariant
What definitely did not happen
Bug class
Causal chain from intended action to system effect
First unintended side effect
Canonical source of truth
Competing sources of truth
Symptom
Trigger
Root cause
Correct layer to fix first
Minimal safe fix
Architectural follow-up
Proposed patch

Frequently asked questions

What does the Root Cause Finder AI skill do?

Why use Root Cause Finder on TypingMind?

Because you install it once and use it with any model. Root Cause Finder 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 Root Cause Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/instructa/agent-skills/tree/main/skills/engineering/root-cause-finder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Root Cause Finder?

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 Root Cause Finder?

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

Is the Root Cause Finder AI skill free?

It is published on GitHub by instructa. Check the repository for licensing terms. 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.

View all

Writing Plans

obra

CommunityPopular

Use when you have a spec or requirements for a multi-step task, before touching code

Ask Matt

Ask which skill or flow fits your situation. A router over the skills in this repo.

Code Review

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what…

Codebase Design

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Root-Cause Finder

Core Instruction

Default Workflow

Questions To Answer In Order

Rules

Hidden Write Checks

Output Format

Frequently asked questions

Related AI Skills

Set up your own AI workspace now