assess

# AI Readiness Assessment + Complexity Hotspot Three artefacts in one pass against a target repo: 1. **Layered contract assessment** - 0-8 score across navigability, runtime liveness, code design, linters, architecture tests, CI, coverage, review bots, and AI project management. 2. **Complexity hotspot SVG** - Codecov-style treemap of the code. Size = LOC. Colour = cyclomatic complexity. Saturation = recent git churn. Vivid red = complex AND active = riskiest to change. 3. **Doc navigability SVG** - a node-graph of the docs. Structure = connectivity (centre = entry, rim = unreachable, dashed ring = orphan); colour = staleness (vivid red = a frozen doc beside churning code = a *lying map*); size = file length. Folds navigability and the decaying-map signal into one artifact. Both SVGs are colour-blind-safe by default (OrRd ramp, no red-green). All land as files inside the target repo. The skill always writes them locally; after writing, **ask the user** whether to open a PR in the target repo with the artefacts. ## The model: truth-pressure, not presence Read this before scoring - it changes how you score. Across every layer, the real signal is never **presence**. It is whether a thing is under **active pressure to stay true**: - Tests keep **behaviour** honest (CI fails when it's wrong). - Retros / feedback loops keep the **process** honest (Layer 8 scores whether retros are *carried out*, not merely present). - Maintenance keeps **docs** honest (a wiki tracked against...