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Engagement Flow

Community
hypnguyen1209
engagement-flow

Use when starting, planning, or running a multi-phase pentest or red-team engagement — to sequence the Cyber Kill Chain phases with quality gates instead of jumping straight to exploitation

Overview

Publisherhypnguyen1209
Repositoryoffensive-claude
Skill nameengagement-flow
Stars
396
Forks
71
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 hypnguyen1209 on GitHub. Read the source before you install it.

Installation

Install the Engagement Flow 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.
    https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/engagement-flow
  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/hypnguyen1209/offensive-claude.git /tmp/offensive-claude
mkdir -p .claude/skills
cp -r /tmp/offensive-claude/skills/engagement-flow .claude/skills/engagement-flow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Engagement Flow 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 Engagement Flow 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 Engagement Flow 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.

Engagement Flow

Overview

A pentest/red-team engagement is a phased pipeline with gates, not a pile of techniques run ad hoc. This skill sequences the 9-phase Lockheed Martin Cyber Kill Chain and routes each phase to its commands, domain skills, and discipline checks. It is the offensive analog of brainstorming → writing-plans → executing-plans: scope the work, plan it, then execute phase by phase.

Don't jump to exploitation. Earlier phases earn the access that later phases need, and each gate keeps quality high before you advance.

The pipeline

dot
digraph killchain {
    rankdir=LR;
    scope -> recon -> weaponize -> deliver -> exploit -> install -> c2 -> actions -> report;
    scope [label="0 SCOPE"]; recon [label="1 RECON"]; weaponize [label="2 WEAPONIZE"];
    deliver [label="3 DELIVER"]; exploit [label="4 EXPLOIT"]; install [label="5 INSTALL"];
    c2 [label="6 C2"]; actions [label="7 ACTIONS"]; report [label="8 REPORT"];
}

Each transition requires a gate (/engage.gate): required artifacts present, findings carry CWE+CVSS+ATT&CK+evidence, and the automated checks pass. Gate FAIL → fix the gap before advancing.

How to run it

  1. Pick the workflow preset for the engagement type (web-app, network, red-team, cloud, mobile, ad-domain, bug-bounty) and drive phases with the /engage.* commands.
  2. Phase 0 (scope): emit .engage/scope/scope.json. REQUIRED: scope-discipline.
  3. Phases 1-7: before any target interaction → scope-discipline; before any outward action → opsec-discipline; invoke the matching domain skill for the technique.
  4. Recall prior intel: at recon/weaponize, /engage.memory recall to start from what worked.
  5. Findings: REQUIRED: finding-discipline — nothing is [CONFIRMED] without proof.
  6. Phase 8 (report): record confirmed findings to engagement-memory; generate the report.
  7. Optional autopilot: engine/engine.py runs the phases under a budget/loop/trace with --resume (/engage.pickup); offensive actions stay operator-gated.

Red Flags — STOP, back up a phase

  • "Let me just start exploiting" (no scope.json / no recon → back to phase 0/1)
  • "Skip the gate, I'll document later" (gates exist so the report is complete and findings are real)
  • "Recon is done, I didn't check prior intel" (run /engage.memory recall)

Quick reference

PhaseCommandDiscipline / tooling
Scope/engage.scopescope-discipline → scope.json
Recon/engage.reconscope-discipline; /engage.memory recall
Exploit/engage.exploitopsec-discipline; finding-discipline
Actions/engage.actionsaction_guard gate; opsec-discipline
Report/engage.reportfinding-discipline; record to memory
Gate / resume/engage.gate, /engage.pickupautomated checks; engine trace

Frequently asked questions

What does the Engagement Flow AI skill do?

Use when starting, planning, or running a multi-phase pentest or red-team engagement — to sequence the Cyber Kill Chain phases with quality gates instead of jumping straight to exploitation

Why use Engagement Flow on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/engagement-flow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Engagement Flow?

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 Engagement Flow?

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

Is the Engagement Flow AI skill free?

Yes. It is published on GitHub by hypnguyen1209 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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