Ai Readiness Assessment

Organization

OneWave-AI

ai-readiness-assessment

Assesses how ready a business is for AI adoption across six dimensions. Evaluates data maturity, tech stack, team skills, process documentation, budget, and culture. Generates a comprehensive ai-readiness-report.md with scores, gap analysis, and recommended starting points. Aligned with OneWave AI's audit methodology.

Overview

Publisher	OneWave-AI
Repository	`claude-skills`
Skill name	`ai-readiness-assessment`
Stars	293
Forks	49
Bundled files	3
License	MIT
Links	Skill source Repository Homepage

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.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Ai Readiness Assessment 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.
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/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/ai-readiness-assessment .claude/skills/ai-readiness-assessment

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

Use it in TypingMind

Enable Ai Readiness Assessment 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 Ai Readiness Assessment 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 Ai Readiness Assessment 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.

AI Readiness Assessment Skill

Conduct a structured, evidence-based evaluation of a business's readiness for AI adoption across six dimensions, then produce a detailed ai-readiness-report.md covering scores, gap analysis, and prioritized next steps. Aligned with OneWave AI's pragmatic, ROI-driven audit methodology.

references/dimensions.md — The six dimensions, full 1-5 scoring rubric, and key questions per dimension.
references/methodology.md — Information-gathering, scoring math and interpretation table, gap analysis, recommendation priorities, company-size and industry tailoring, and conversation flow.
references/output-template.md — The complete ai-readiness-report.md structure to fill in.

Workflow

Gather context. Collect information through conversation, document review, and codebase analysis. See references/methodology.md (Phase 1) for channels and the question set in references/dimensions.md.
Score the six dimensions. Rate each from 1 to 5 against the rubric in references/dimensions.md. Be honest and conservative, use half-points for nuance, and record the evidence behind every score.
Calculate the overall score. Apply the weighted formula and map it to a readiness level using the table in references/methodology.md (Phase 2).
Run the gap analysis. For each dimension below 4.0, document current state, target state, the gap, its impact, and the effort to close it (Phase 3).
Build recommendations. Produce prioritized actions across the five OneWave priority tiers, tailoring for company size and industry (Phase 4 and tailoring section).
Generate the report. Write ai-readiness-report.md following references/output-template.md, then highlight the top 3 immediate actions.

The Six Dimensions

Dimension	Weight
Data Maturity	25%
Technology Stack	20%
Team Skills and Capacity	20%
Process Documentation	15%
Budget and Resources	10%
Organizational Culture	10%

See references/dimensions.md for the full rubric and questions.

Core Rules

Never inflate scores. A business that scores 2.0 needs to hear that honestly; false optimism wastes money and time.
Always provide evidence. Back every score with specific observations, not assumptions.
Be actionable. Pair every identified gap with a concrete recommendation.
Respect budget realities. Include cost-appropriate options; not every organization needs enterprise-grade solutions.
Use no jargon without explanation. The report is read by business leaders, not only technologists.
Flag deal-breakers. When a dimension scores 1.0, state explicitly that AI initiatives should not begin until it is addressed.
Consider the full cost. Include ongoing costs (maintenance, retraining, monitoring), not just implementation.
Recommend the right AI. Match recommendations to actual readiness; do not recommend deep learning to a company that has not consolidated its data.
Maintain OneWave AI alignment. Frame all recommendations within pragmatic, ROI-driven AI adoption. Avoid hype; focus on business value.
Use no emojis. Keep all output professional and text-based.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ai Readiness Assessment AI skill do?

Why use Ai Readiness Assessment on TypingMind?

Because you install it once and use it with any model. Ai Readiness Assessment 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 Ai Readiness Assessment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/ai-readiness-assessment. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ai Readiness Assessment?

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 Ai Readiness Assessment?

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

Is the Ai Readiness Assessment AI skill free?

Yes. It is published on GitHub by OneWave-AI 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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Ai Readiness Assessment

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AI Readiness Assessment Skill

Contents

Workflow

The Six Dimensions

Core Rules

Bundled files

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AI Readiness Assessment Skill

Contents

Workflow

The Six Dimensions

Core Rules

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now