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Run an assessment

Prerequisites

  • The plugin installed in Copilot CLI or Claude Code.
  • Your terminal / tool open with the target repository as the working directory, so the scan can see its files.

Run it

Use the slash command:

/ai-readiness-assess

Or trigger it by natural language — the skill responds to phrases like:

assess our AI readiness · where are we on the framework? · check our habitat maturity · score our AI maturity

What happens

  1. Discovery — a report of the habitat documents and signals found (with paths) and the ones absent.
  2. Questions — 3–5 clarifying questions, asked one at a time, to place the behavioural dimensions the filesystem can't show. Answer each before the next is asked.
  3. Assessment — all fourteen model dimensions placed L1–L5, the cognitive level, and the Habitat Build Gap.
  4. Report — written to assessments/YYYY-MM-DD-assessment.md, with a short summary in the chat.

See the full assessment output structure for a section-by-section breakdown.

Tips

  • Run it from the repo root. Running from a subdirectory hides habitat documents and skews the result.
  • If two files seem to fill the same role (say two candidate instruction files), the assessment will stop and ask which is canonical rather than guess. Answer it — silent picks produce confidently-wrong assessments.
  • Commit the report. assessments/YYYY-MM-DD-assessment.md is a durable record; committing it lets you track movement over time.

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