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.
SkillScore91Maintained
Automatic
◆AI Engineer pack
Last verified 8/24/2026
What it changes
Passed 21 of 23 test cases with the skill, and 11 of 23 without it.
Without skill48%
With skill91%
Checks it passed that the model alone missed
The generated report contains zero emojis.
The report evaluates Data Maturity with a 25% weight.
The document explicitly highlights the top 3 immediate actions.
and 10 more in the full report
10 fixed11 passed either way2 still failing0 broke
Pass-rate lift
+43 pp
Tokens
+51%
Agent turns
0%
Response time
+24%
Model gemini-3.6-flashMeasured 8/24/2026v121 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 10
Prompt
We are a mid-sized logistics company with 250 employees planning to introduce AI for route optimization and demand forecasting. Currently, our tracking data resides in legacy SQL databases and spreadsheets, our IT staff lacks machine learning experience, operational workflows are only partially documented, and executive leadership set aside $150k for tech updates. Please conduct an objective AI readiness evaluation using these details and generate a markdown document titled ai-readiness-report.md. The report should present evaluated scores across the key business and technical dimensions, an analysis of critical gaps, and a prioritized action plan highlighting top immediate steps.
What was checked, without and with the skill
Checked
Without skill
With skill
The report evaluates Data Maturity with a 25% weight.
Missed
Passed
The report highlights the top 3 immediate actions at the conclusion.
Missed
Passed
case-01 · gemini-3.6-flash · 8/24/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md44 lines4 files
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.
Contents
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.