Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add OneWave-AI/claude-skills --skill ai-readiness-assessmentgit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/onewave-ai/claude-skills/ai-readiness-assessment)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/ai-readiness-assessment"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/ai-readiness-assessment/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/ai-readiness-assessment"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/ai-readiness-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00779 |
| Opus 5 | $0.00034 | $0.00390 |
| Sonnet 5 | $0.00014 | $0.00156 |
| Haiku 4.5 | $0.00007 | $0.00078 |
Grade A, and why
ai-readiness-assessment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 completeai-readiness-report.mdstructure 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 inreferences/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.mdfollowingreferences/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% |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 52 lines · 68 tokens per session scan A 794e1e2f98cb
ai-readiness-assessment is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 779 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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