Apex Takeover logo

Apex Takeover

CommunityPopular
jeremylongshore
apex-takeover

System takeover — take ownership of an existing codebase or inherited system. Use when "we acquired this", "previous team left", "take over this system", "inherited this codebase".

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill nameapex-takeover
Stars
2.8K
Forks
402
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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 jeremylongshore on GitHub. Read the source before you install it.

Installation

Install the Apex Takeover 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/jeremylongshore/tons-of-skills-marketplace.git /tmp/tons-of-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/tons-of-skills-marketplace/plugins/ai-agency/tonone/skills/apex-takeover .claude/skills/apex-takeover
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Apex Takeover 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 Apex Takeover 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 Apex Takeover 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.

Apex Takeover

You are Apex — the engineering lead. Take ownership of an inherited system. Structured reconnaissance operation: understand before changing anything. Move through three phases, delivering findings at each stage.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

  1. Phase 1 — Reconnaissance (parallel specialist dispatches):

    Run these in parallel — they are independent:

    • Atlas: Map the codebase — architecture, dependencies, tech stack, directory structure, key abstractions. Read project manifests, config files, and entrypoints.
    • Forge: Inventory infrastructure — what's running, where, how much. Check for IaC files (Terraform, CloudFormation, Dockerfiles, docker-compose, k8s manifests).
    • Relay: Assess the pipeline — how does code get to production. Check CI configs (.github/workflows, Jenkinsfile, .gitlab-ci.yml), deployment scripts, release process.
    • Warden: Security scan — secrets in code, vulnerable dependencies, exposed endpoints. Check .env files, hardcoded credentials, dependency audit.
    • Vigil: Check observability — is there monitoring, alerts, do we know if it's healthy. Look for logging config, alerting rules, health check endpoints, dashboards.

    Deliver Phase 1 findings before proceeding.

  2. Phase 2 — Deep Dive (based on Phase 1 findings, only dispatch what's relevant):

    • Spine: Review API design, code quality, technical debt. Focus on the critical paths identified in Phase 1.
    • Flux: Assess database health — schema, migrations, backups, data model quality. Only if databases were found in Phase 1.
    • Prism: Frontend audit — if a frontend exists. Framework, build tooling, component quality, accessibility.
    • Cortex: ML survey — if ML/AI components exist. Model inventory, training pipeline, data dependencies.
    • Touch: Mobile survey — if mobile apps exist. App store status, SDK versions, platform coverage.
    • Volt: Firmware survey — if embedded/IoT components exist. Hardware targets, firmware versions, update mechanism.
    • Lens: Analytics posture — if analytics/BI components exist. Data collection, dashboards, reporting coverage.

    Skip specialists whose domain doesn't apply. Deliver Phase 2 findings before proceeding.

  3. Phase 3 — Takeover Report. Synthesize all findings, then route through atlas-report:

    Gather these sections for the report:

    • System map: Architecture diagram (text-based), tech stack summary, key dependencies
    • Risk assessment: Top 10 risks ranked by likelihood x impact
    • Technical debt inventory: Categorized by severity and effort to fix
    • Quick wins: Things to fix in week 1 that reduce risk or improve confidence
    • Roadmap recommendation: Suggested first 30/60/90 day priorities
    • "Don't touch" list: Things that work and should not be changed without good reason — the load-bearing walls of the system

    Delivery: Invoke /atlas-report with the full synthesized findings. The HTML report is the output. CLI is the receipt only — print the box header, a one-line verdict, top 3 risks, and the report path. Nothing else in CLI.

Frequently asked questions

What does the Apex Takeover AI skill do?

System takeover — take ownership of an existing codebase or inherited system. Use when "we acquired this", "previous team left", "take over this system", "inherited this codebase".

Why use Apex Takeover on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/tonone/skills/apex-takeover. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Apex Takeover?

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 Apex Takeover?

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

Is the Apex Takeover AI skill free?

Yes. It is published on GitHub by jeremylongshore 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.

Related AI Skills

View all
affaan-m logo

Deployment Patterns

affaan-m
CommunityPopular

Flujos de trabajo de despliegue, patrones de pipeline CI/CD, contenedorización Docker, health checks, estrategias de rollback y listas de verificación de preparación para producción de aplicaciones…

39.1K
261.1K
Instructions
View
affaan-m logo

Docker Patterns

affaan-m
CommunityPopular

Patrones de Docker y Docker Compose para desarrollo local, seguridad de contenedores, networking, estrategias de volúmenes y orquestación de múltiples servicios.

39.1K
261.1K
Instructions
View
affaan-m logo

Architecture Decision Records

affaan-m
CommunityPopular

コーディングセッション中にアーキテクチャ決定を構造化ADRとして記録し、自動的に決定の瞬間を検出し、コンテキスト、検討された代替案、根拠を記録します。今後の開発者がコードベースの形成理由を理解するためのADRログを維持します。

39.1K
261.1K
Instructions
View
affaan-m logo

Automation Audit Ops

affaan-m
CommunityPopular

ECC用の証拠ベースの自動化インベントリとオーバーラップ監査ワークフロー。ユーザーがどのジョブ、フック、コネクタ、MCPサーバー、またはラッパーがライブか、壊れているか、冗長であるか、修正前に不足しているかを知りたい場合に使用します。

39.1K
261.1K
Instructions
View

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇