Use ai-readiness-assessment

Score an organisation's or team's readiness to adopt AI tooling across six gating dimensions

Score an organisation's or team's readiness to adopt AI tooling across six gating dimensions — data, tooling, skills, governance, process, and culture — with an evidence line per score and the blocking gaps ranked by what stops adoption first.

Reach for it when the user asks "are we ready for AI", wants an AI maturity or readiness baseline, or needs to know what to fix before rolling tools out. Do NOT use to pick which use cases to build (that's ai-use-case-triage) or to plan the rollout itself (that's ai-adoption-rollout).

Install it

npx skilldrop-cli install ai-readiness-assessment                 # Claude Code, your user folder
npx skilldrop-cli install ai-readiness-assessment --project       # Claude Code, this repo
npx skilldrop-cli install ai-readiness-assessment --ide cursor    # or kiro, codex, antigravity, copilot

It is part of the AI engineering pack: --pack ai-engineering installs it with its neighbours.

Ask for it

Say it the way you would to a colleague. Requests like these route to it:

• "Are we ready to adopt AI?"
• "Assess our AI maturity and tell me what's blocking us"
• "Give me an AI readiness baseline for our engineering org"
• "What do we need to fix before rolling out AI tools?"

Requests like these belong to a different skill, so it shouldn't answer them:

• "Which AI use cases should we build first?"
• "Plan how we roll this tool out to 200 people"
• "Write our AI acceptable-use policy"

If another skill answers instead, ask for this one by name: "use ai-readiness-assessment".

Check what you get

A good result:

• Every score carries an evidence line. A number with nothing behind it is the failure mode this skill exists to prevent — cut it or mark it [insufficient evidence].
• All six dimensions appear, including the ones the input is thin on. Silence on a dimension reads as a pass, and that's how readiness reports mislead.
• Gaps are ranked by blocking order, not by score. The lowest number is not automatically the first problem, and the plan must say why.
• Every gap has a first action and an owner role — a role, never a person's name, so the assessment doesn't go stale when someone changes teams.
• The posture sentence takes a position and names the condition that would change it. "It depends" is a refusal to do the job.
• No invented facts. Where the input is silent, say so; a fabricated observation is worse than an admitted gap.

Use something else when

• Choosing which workflows to automate — that's ai-use-case-triage.
• Planning the rollout once you've decided to go — that's ai-adoption-rollout.
• Writing the rules for what people may put into a tool — that's ai-usage-policy.
• A market or competitive question ("should we enter this space?") — that's strategy-analysis.
• Measuring adoption that has already happened — that's ai-usage-report.
• Assessing how far an engineering team's agent practice has actually got — agents in flight, who writes the code, what still gets reviewed — that's agent-adoption-stage. It's the orthogonal axis: this skill scores whether the organisation can adopt at all; that one scores how far the practice has got. A team can be governance-ready and stuck at stage 1, or running ten agents with no policy at all — run both when the answers disagree.

Next

• SKILL.md, the instructions the agent reads
• Its page on the site
• Related: agent-adoption-stage, ai-adoption-rollout, ai-usage-policy, ai-usage-report, ai-use-case-triage, strategy-analysis

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