This public repo shape is based on a scan of strong public AI infrastructure repos, including Guardrails AI, Langfuse, Portkey, Letta, AgentScope, Invariant, LLM Guard, Tencent AI-Infra-Guard, and Prompt Injector.
- lead with a category claim, not a theory claim
- make time-to-value obvious
- put product and operator value before proof
- use the repo itself as marketing, onboarding, and trust surface
- own one wedge instead of explaining five products at once
Ardur should not open as:
- a paper repo
- a benchmark repo
- a protocol archive
- a dump of internal history
Ardur should open as:
- a runtime governance layer
- an evidence layer
- a proof-backed engineering project
The public wedge is narrower than the internal monorepo story:
- govern agent actions against a declared mission
- emit verifiable runtime evidence
- prove claims with reproducible artifacts
That is more distinctive than competing on "guardrails" alone.
Ardur is the public product and repo name.
VIBAP, MCEP, and related protocol names remain useful where they identify
the implementation lineage, evidence model, or protocol research roots. The
public repo should preserve those names when they are technically meaningful
and avoid obsolete product codenames in public-facing copy.
The repo includes:
- intent
- status
- roadmap
- public v0.1 specs
- curated Python and Go runtime imports
- the Ardur Personal Hub service and Claude Code plugin
- runnable LangChain, LangGraph, and AutoGen framework examples plus the Ardur Personal browser extension, desktop-observe adapter, native-host, and offline/no-key OpenAI Agents SDK and Google ADK fixtures
- dedicated Python and Go CI workflows
- the Hugo public evidence-site source
- selected archival recordings
The remaining work is a tagged packaged distribution, end-to-end proof paths that retire the archival-only media caveat, live-provider OpenAI Agents SDK and Google ADK wrapper evidence beyond the current no-key fixtures, and broader deployment validation.