diff --git a/README.md b/README.md index 7f1bf8d..223975f 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,8 @@ -# agent-vm +# BoundaryKit + +> **BoundaryKit** (formerly **agent-vm**) is a public reference architecture for governing untrusted autonomous workloads with explicit runtime boundaries, promotion controls, rollback paths, and evidence-backed validation. +> +> The project repository and public site remain hosted at `sambegui/agent-vm` and `agent-vm.sabe.dev`. **A framework-agnostic sandbox skeleton for governed AI-agent workloads that are treated as untrusted.** diff --git a/docs/architecture/00-overview.md b/docs/architecture/00-overview.md index d6b6d3f..b79462b 100644 --- a/docs/architecture/00-overview.md +++ b/docs/architecture/00-overview.md @@ -6,7 +6,7 @@ Most enterprise AI usage still happens through isolated browser tabs or ad hoc a fragments context, hides execution state, and gives reviewers little evidence about what ran, what authority was available, or how recovery would work. -`agent-vm` presents a governed runtime architecture for autonomous AI-agent workloads that are +`BoundaryKit` presents a governed runtime architecture for autonomous AI-agent workloads that are treated as untrusted. Agents can process approved messages, attached documents, external links, transcripts, API responses, and structured outputs, but the platform does not trust the agent or the inputs it receives. diff --git a/docs/evidence/governed-agent-workload-case-study.md b/docs/evidence/governed-agent-workload-case-study.md index 63b049c..78d1b67 100644 --- a/docs/evidence/governed-agent-workload-case-study.md +++ b/docs/evidence/governed-agent-workload-case-study.md @@ -1,6 +1,6 @@ # Case Study: Treating an Agent as an Untrusted Workload -This case study is an illustrative, vendor-neutral walkthrough for reading the `agent-vm` +This case study is an illustrative, vendor-neutral walkthrough for reading the `BoundaryKit` architecture. It is not a product claim, customer deployment claim, or proof that a production workload is ready. Its purpose is to show how the repository's trust boundaries, operational controls, and evidence model apply when an autonomous AI-agent workload handles untrusted input. diff --git a/platform/tests/docs-public-contract-test b/platform/tests/docs-public-contract-test index eea9482..1b1dabb 100644 --- a/platform/tests/docs-public-contract-test +++ b/platform/tests/docs-public-contract-test @@ -94,9 +94,9 @@ require_text "$ROOT/site/index.html" 'rel="canonical"' require_text "$ROOT/site/index.html" 'property="og:title"' require_text "$ROOT/site/index.html" 'name="twitter:card"' require_text "$ROOT/site/index.html" 'aria-controls="nav-links"' -require_text "$ROOT/site/docs/architecture/00-overview.html" "