Semantic Kernel
A source-qualified lifecycle governance mapping for Semantic Kernel agent and orchestration patterns, included because official Microsoft sources support the ecosystem context.
Independent lifecycle governance lens.
This page is independent lifecycle governance analysis. It is not Microsoft documentation, Microsoft affiliation, framework scoring, legal advice, certification, legal compliance proof, or procurement guidance.
These pages apply GAIC lifecycle governance concepts to extended ecosystems. They are not GAIC scored assessments, vendor rankings, procurement recommendations, certifications, legal compliance proof, official vendor documentation, or vendor affiliations.
Ecosystem context
Semantic Kernel is treated here as an agent and orchestration SDK context. The lifecycle governance question is how plugins, agent interactions, process orchestration, tool calls, filters, observability, human input, and accepted outcome remain tied to responsibility records.
R3F uses Microsoft Learn and Microsoft GitHub sources to establish Semantic Kernel as an AI agent and orchestration SDK context. The page does not compare Semantic Kernel against Microsoft Agent Framework, AutoGen, or other frameworks.
Lifecycle governance questions
- What authority boundary governs consequential work?
- What evidence chain survives tool, model, agent, or runtime action?
- What accepted outcome state is defined, and who may accept it?
- How are rollback, remediation, dispute, and substitution handled?
- Which human or organizational role owns lifecycle responsibility?
- Which plugin or function calls are allowed under the approved work scope?
- What filter, observability, or review evidence is sufficient for acceptance and remediation?
Related Missing Regulatory Objects
These concepts are governance lenses for the mapping. This page does not claim the ecosystem has or lacks a feature unless the statement is supported by an official source.
RCCS-M / ALCS relevance
RCCS-M is relevant as a governance-coverage lens for lifecycle responsibility objects. ALCS is relevant as a lifecycle-coherence lens across intent, authority, evidence, acceptance, dispute, remediation, and closure. This R3F mapping is author-analytical and source-qualified, not a GAIC-scored assessment.
Harness Engineering relevance
Harness Engineering is relevant because SDK-level orchestration needs surrounding policy, context boundaries, tool-call authority, evidence capture, review gates, and closure records.
Protocol path
MPLP is one protocol path for expressing lifecycle responsibility semantics around agentic work. It is not required, exclusive, certified, regulator-approved, vendor-affiliated, or already an industry standard.
White paper source trace
Semantic Kernel is treated as an adjacent framework/orchestration SDK mapping, not a GAIC-scored system or Microsoft documentation.
This page is adjacent to GAIC, not a GAIC-scored assessment. It uses MRO, RCCS-M, and ALCS as lifecycle governance lenses for an ecosystem context established by official sources.
Use the trace to ask how tool access, agent delegation, model/runtime substitution, evidence, accepted outcome, rollback, and remediation would survive across the workflow.
This mapping is source-qualified and non-GAIC-scored. It is not vendor documentation, vendor affiliation, product scoring, legal advice, certification, legal compliance proof, procurement guidance, or a claim that MPLP is required.
Official sources consulted
- Semantic Kernel overview Official Microsoft Learn overview reviewed.
- Semantic Kernel Agent Framework Official Microsoft Learn agent framework documentation reviewed.
- Semantic Kernel GitHub repository Official Microsoft GitHub repository reviewed.