Chris0x88

INSTALL · Onboarding Kit

The kit is a folder of markdown skill files. Any modern AI agent that can read markdown can run it. Below are the exact invocations for the four common harnesses.

Claude Code

The recommended setup.

Option A · Run in place

cd /path/to/Chris0x88.github.io/consultant/onboarding-kit
claude

Then in the Claude Code session:

Read kit.skill.md and run the onboarding kit. Write all output files to the current directory.

Claude Code will pick up the skill, walk through the phases, and produce your four output files.

Option B · Install as a permanent skill

mkdir -p ~/.claude/skills/onboarding-kit
cp -r /path/to/Chris0x88.github.io/consultant/onboarding-kit/* ~/.claude/skills/onboarding-kit/

Then from any project:

/skills

Run the onboarding-kit skill.

This makes the kit available everywhere without re-cloning.

OpenAI Codex

Codex reads markdown skills out of the working directory by default.

cd /path/to/Chris0x88.github.io/consultant/onboarding-kit
codex

Then:

Read kit.skill.md and follow the onboarding-kit phases. Save outputs locally.

For a permanent install across projects, drop the kit into Codex’s user skills location (check your Codex version’s docs for the exact path; recent versions look in ~/.codex/skills/).

Hermes

Hermes (Nous Research) accepts markdown skills via its skill loader.

hermes --skill /path/to/Chris0x88.github.io/consultant/onboarding-kit/kit.skill.md

Once running:

Run the onboarding kit.

Hermes will follow the phase instructions in kit.skill.md and pull in the sub-skills as needed.

Generic

The kit is just markdown. If your agent can read instructions from a folder, you can run the kit by:

Pointing the agent at kit.skill.md as the entry point.
Letting the agent read the referenced sub-skills (skills/*.md) and the interview script (interview.md) on demand.
Telling it to write outputs to the working directory.

Tested compatible:

Claude Code (any version 2025.10+)
OpenAI Codex CLI (any current version)
Hermes (Nous Research)
Custom agents using the standard markdown-skill convention

Not tested but should work:

Open Interpreter (with file access)
Aider (loaded as a context file)
Cursor (paste kit.skill.md into chat as system prompt)

Choosing a model

The kit uses tool calls, web research, and structured output. A capable frontier model is recommended.

Phase	Recommended model
Interview	Claude Sonnet 4.6 or higher · GPT 5 or higher
Business research	Same. Web access required.
Brand capture	Same. Web access required.
Stack detection	Any. Lightweight read-only ops.
Report generation	Claude Opus 4.7 (best prose) or Sonnet 4.6 (cheaper, almost as good)

If you only have one model available, use Claude Sonnet 4.6 across the whole run. It’s the best generalist for this work right now.

What if my agent doesn’t have web access?

Skip the business-research and brand-capture phases, or feed the agent your own scraped data:

I don’t have web access. Here’s our website HTML and our LinkedIn About page. Use these as the inputs for business-research and brand-capture, then continue with the rest of the kit.

The interview, stack detection, and report generation phases work fully offline.

Troubleshooting

Agent says it can’t find a sub-skill. Make sure the working directory is consultant/onboarding-kit/ so relative paths resolve.
Stack detection reports nothing. Run the agent under a shell where your provider env vars are set. Check with env | grep -i api first.
Report HTML looks plain. The template uses inline styles for portability. If you want it themed, edit templates/report.html before running phase 5.
Anything else. Open an issue on the Chris0x88.github.io repo or just email me.