Evanflow Debug

Community

evanklem

evanflow-debug

Root-cause discipline for bugs, test failures, and unexpected behavior. Embedded grill on the hypothesis before writing fix code. Use when encountering any bug, failing test, or behavior that doesn't match expectation.

Overview

Publisher	evanklem
Repository	`evanflow`
Skill name	`evanflow-debug`
Stars	418
Forks	18
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 evanklem on GitHub. Read the source before you install it.

Installation

Install the Evanflow Debug 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/evanklem/evanflow/tree/main/skills/evanflow-debug
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/evanklem/evanflow.git /tmp/evanflow
mkdir -p .claude/skills
cp -r /tmp/evanflow/skills/evanflow-debug .claude/skills/evanflow-debug

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

Use it in TypingMind

Enable Evanflow 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 Evanflow 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 Evanflow 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.

EvanFlow: Debug

Vocabulary

See evanflow meta-skill.

When to Use

Test failing
User reports unexpected behavior
Production error
Code does the wrong thing under specific conditions
Anything where the immediate symptom isn't the root cause

SKIP when: the cause is obvious and the fix is one line. Don't ceremonialize trivial bugs.

The Flow

1. Reproduce

Get the exact reproduction: input, environment, steps
Reproduce locally if possible. If you can't reproduce, the bug is unverified — say so before proceeding.

2. Form a Hypothesis

State the hypothesis explicitly:

"I think the bug is in : because when X happens, Y is supposed to happen but instead Z does."

A vague "probably the validation" is not a hypothesis.

3. Embedded Grill — Challenge the Hypothesis

Before writing any fix, ask:

Symptom vs. cause: "Is this where the bug manifests, or where it originates? Trace one step further upstream."
Coverage: "What other code paths share this root cause? Will the fix here leave those paths broken?"
Reversibility: "Does the fix have the same blast radius as the bug, or wider?"
Test gap: "Why didn't a test catch this? Is the test missing, wrong, or misaligned with real behavior?"
Domain check: "Is the bug actually behaving correctly per spec, and the spec is wrong?"

4. Verify the Hypothesis Before Fixing

Add an instrument (log, breakpoint, test assertion) that proves the hypothesis right or wrong. Watch the instrument fire. If it doesn't, the hypothesis is wrong — go back to step 2.

5. Write a Failing Test First

The test should fail because the bug exists. This is a vertical-slice TDD application — see evanflow-tdd.

6. Fix at the Root

Fix where the root cause originates, not where the symptom appears. If the fix is far from the symptom, leave a comment explaining the WHY (this is one of the few cases where a code comment earns its keep).

7. Verify the Test Passes

Run the test. Run the broader suite. Confirm no regressions.

Hard Rules

No fix without a failing test that demonstrates the bug. (Same TDD principle as evanflow-tdd.)
Fix the root, not the symptom. Symptom-fixes are how bugs metastasize.
Never auto-commit. A fix gets staged; user confirms before commit.
If you can't reproduce, say so. Don't fix invisible bugs.

Hand-offs

Fix complete, tests pass → if mid-plan, return to evanflow-executing-plans. If standalone debug, report what was fixed and STOP. The user decides whether to commit or take further action.
Discovered an architectural issue → evanflow-improve-architecture
Discovered the spec is wrong → evanflow-brainstorming to align on intended behavior

Frequently asked questions

What does the Evanflow Debug AI skill do?

Why use Evanflow Debug on TypingMind?

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

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

Which AI models can use Evanflow 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 Evanflow Debug?

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

Is the Evanflow Debug AI skill free?

It is published on GitHub by evanklem. 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

EvanFlow: Debug

Vocabulary

When to Use

The Flow

1. Reproduce

2. Form a Hypothesis

3. Embedded Grill — Challenge the Hypothesis

4. Verify the Hypothesis Before Fixing

5. Write a Failing Test First

6. Fix at the Root

7. Verify the Test Passes

Hard Rules

Hand-offs

Frequently asked questions

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