Known
- The local setting is reversible.
- The active policy requires an exact host grant.
- One external-call unit is reserved for reconciliation.
You are sitting where an AI agent sits. It starts from a bounded view of the situation, holding only what this task needs, and sees only the actions open to it right now. Authority, assurance, cost, unknowns, and evidence stay visible before any plan exists.
This is a teaching simulation. The situation, moves, and costs are fixed in the page, every effect is simulated, and nothing leaves your browser.
Speed preference conflicts with the firm proof-before-completion boundary.
local read
No authority is inferred from capability discovery.
1/ 3
Moves available now under the current authority; the others need a host grant or authority this demo does not have.
The preference for speed still clashes with the rule that nothing counts as done until it is proven. The view records the clash rather than settling it, and the agent can raise an objection before it plans, acts, proves, or learns.
Each kind of assurance keeps its own axis. A schema digest says nothing about who published the schema, and neither settles whether the result can be trusted.
The schema digest and local candidate lineage are declared. Nothing in this demo checks them.
No publisher signature is loaded.
Local reads are present. Writes remain gated.
No effect has crossed the simulated effect boundary.
Nothing yet proves the release channel was actually set.
No one has judged whether to trust the result, and integrity and authority alone cannot settle it.
Pick a failure to inject, or none, then use the buttons below to walk one change through the loop. Every effect is simulated, and no scenario grants real authority.
vcp:artifact:situation:situation.demo.release Bounded orientation root
1 situation.compiledCursor: cursor.demo.1
external calls
external calls
calls avoided
call remaining
Spent so far counts both runs. The baseline is what those two runs would cost without a saved procedure, so the difference appears once the second run is done. These numbers come from a fixed teaching trace. They say nothing about latency or model quality in production.
It records this run so it can be replayed, and leaves out live grants, credentials, and raw private context.
The JSON validates against the draft Agent Runtime schema and names every artifact it depends on.
sha256:920b308c2438d47ac234240fc35e088afa4dd6621e3e1884da993db9dbce1e01This is an educational, source-level reference simulation. It carries no live grant and makes no deployment, publication, ratification, or production assurance claim.