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Investigate

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Houseofmvps
investigate

Root cause investigation — structured debugging with module freeze. No fixes without investigation. Use when encountering any bug, error, or unexpected behavior.

Overview

PublisherHouseofmvps
Repositoryultraship
Skill nameinvestigate
Stars
122
Forks
14
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Houseofmvps on GitHub. Read the source before you install it.

Installation

Install the Investigate 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/Houseofmvps/ultraship.git /tmp/ultraship
mkdir -p .claude/skills
cp -r /tmp/ultraship/skills/investigate .claude/skills/investigate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Investigate 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 Investigate 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 Investigate 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.

Investigate — Root Cause Analysis

Investigation is the discipline of understanding a problem before fixing it. This skill enforces a strict protocol: no fixes until the root cause is found.

Enforced: while this skill is active, Edit, Write, and NotebookEdit are removed via disallowed-tools. The no-fixes rule is a hard constraint here, not a request. Once you have found and stated the root cause, conclude the investigation — the fix happens as a separate step outside this skill.

Announce at start: "I'm using the investigate skill — no fixes until we find the root cause."

The Iron Law

┌──────────────────────────────────────────────┐
│  NO FIXES WITHOUT ROOT CAUSE INVESTIGATION   │
│                                              │
│  If you haven't found the root cause,        │
│  you cannot propose a fix.                   │
└──────────────────────────────────────────────┘

This is not a suggestion. This is a hard constraint. Guessing causes more bugs than it fixes.

Process

Phase 1: Scope Lock

Before investigating, lock the investigation scope to prevent it from sprawling:

  1. State the symptom — What exactly is broken? Be precise.
  2. Identify the module — Which part of the codebase is affected?
  3. Freeze to module — Investigation stays within this module until evidence points elsewhere.

Example:

Symptom: API returns 500 on POST /api/webhooks
Module: packages/api/src/routes/webhooks.ts
Freeze: Investigation limited to webhook handler + its direct dependencies

Why freeze? Without scope, investigation becomes exploration. Exploration finds interesting things but doesn't fix bugs.

Phase 2: Evidence Collection

Gather evidence BEFORE forming any hypothesis:

  1. Read the error — Full stack trace, error message, error code. Not a glance — read every line.

  2. Reproduce — Can you trigger it reliably? What are the exact steps?

    • If reproducible: proceed
    • If intermittent: gather more data points, don't guess
  3. Check the timeline — What changed recently?

    bash
    git log --oneline -20
    git diff HEAD~3
  4. Trace the data flow — Follow the data from input to error:

    • What value enters the function?
    • What transformation happens?
    • Where does it break?
    • Trace BACKWARD from the error to the source
  5. Check boundaries — For multi-component systems, verify data at each boundary:

    • API → service: is the request correct?
    • Service → database: is the query correct?
    • Database → response: is the result expected?

Phase 3: Hypothesis

Form ONE hypothesis based on evidence:

"I think [X] is the root cause because [evidence Y shows Z]"

Requirements:

  • Must be specific (not "something is wrong with auth")
  • Must be supported by evidence collected in Phase 2
  • Must be testable with a single, minimal change

Phase 4: Test

Test the hypothesis with the SMALLEST possible change:

  1. Make ONE change
  2. Run the reproduction steps
  3. Did it fix the issue?
    • Yes → Proceed to Phase 5
    • No → Return to Phase 2 with new information. Do NOT add more fixes.

Critical: If 3 hypotheses fail, STOP. The problem is likely architectural, not a simple bug. Discuss with the user before attempting fix #4.

Phase 5: Fix

Now — and only now — implement the proper fix:

  1. Write a failing test that reproduces the exact bug
  2. Implement the fix — address the root cause, not the symptom
  3. Verify the test passes
  4. Run the full test suite — ensure no regressions
  5. Save the learning — record what you found for future reference:
    bash
    node ${CLAUDE_PLUGIN_ROOT}/tools/learnings-manager.mjs save --title "Root cause of webhook 500" --body "The webhook handler wasn't awaiting the database write, causing a race condition with the response" --tags "debugging,webhooks,async"

Red Flags

If you catch yourself doing any of these, STOP and return to Phase 2:

  • "Let me just try this quick fix"
  • "It's probably X, let me change it"
  • "I'll add multiple changes and see which works"
  • "I don't fully understand but this might work"
  • "Here are 3 possible fixes" (without investigation)
  • Proposing solutions before tracing the data flow

Integration with Guard

For critical systems, activate /guard before investigating to prevent accidental changes:

/guard → /investigate → fix → /canary

Guard ensures no destructive commands run during investigation, and canary verifies the fix in production.

Relationship to Systematic Debugging

This skill shares principles with ultraship:systematic-debugging but adds:

  • Module freeze — scoped investigation prevents sprawl
  • Learning capture — every investigation produces a learning
  • Guard integration — safety during critical system debugging
  • Escalation protocol — clear rules for when to stop and rethink

Frequently asked questions

What does the Investigate AI skill do?

Root cause investigation — structured debugging with module freeze. No fixes without investigation. Use when encountering any bug, error, or unexpected behavior.

Why use Investigate on TypingMind?

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

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

Which AI models can use Investigate?

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 Investigate?

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

Is the Investigate AI skill free?

Yes. It is published on GitHub by Houseofmvps 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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