Read the Star, one state at a time. The 64 vertices describe positions in the agentprivacy model. Import your City Key to see its descriptions, attention and recorded activity against that geometry.
This is the detailed reading of your key’s perspective. A lit vertex records something in the loaded artefact; its meaning and evidence still matter. How the Star represents you →
This renders V(π,t) = P1.5 · C · Q · S · … · Φ_agent(Σ) · … · T∫(π) — a holographic field on the 96-edge boundary ∂M. The codex shows the lattice ℒ and the path; the 3D /star manifold shows the agent axis and the boundary.
focus (vertex → amount). Here it glows as an inner gold aura — heavier where you've committed more attention. The feedback between the two interfaces.
off-axisΦv5 = Φ_agent · Φ_data · Φ_inference (multiplicative — any axis → 0 collapses value). Only Φ_agent is drawn; the other two axes are off-screen.
κ · content identityexported keys carry kappa = sha256:H(canonical form) — a UOR-ADDR κ-label on the sha256 axis. On import the label is re-derived and checked: identity is content, not location. The key is what it says, wherever it travels.
✍️ inscriptiona proven blade — focus walked to ✓, or achievement-lit ✦ — accepts your own reading. Writing changes the content; the content drifts the κ; the sigil relights. These local activity markers enable inscription here; they do not independently verify learning or City standing.
Tags follow the V5.4 spec: [proven] / [canon] / [conjecture]; conjecture authority now lives in the V6 register — when prose and register disagree, the register wins. Implementation references at Labs; the model at agentprivacy.ai/model.