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Migaki is an execution optimizer for agentic systems.
It represents model, tool, retrieval, context, validation, and policy work as portable execution graphs; transforms those graphs under explicit cost, latency, quality, and governance constraints; lowers them into provider-specific runtimes; and emits evidence for every optimization.
The project is not trying to replace agent frameworks, gateways, workflow engines, eval platforms, or observability systems. Migaki sits in the missing middle between logical agentic workflows and concrete execution infrastructure.
- Project Scope defines what Migaki is, what it is not, and what must stay out of v0.
- Whitepaper Notes captures the working thesis, the strongest claims, and the places that need pressure-testing.
- v0 Roadmap describes the first implementation target.
- Repository Shape maps the intended package layout.
- mIR describes the Migaki intermediate representation.
- Optimization Passes lists the first execution transformations.
- Execution Evidence Bundles defines the audit and replay artifact every optimized run should produce.
- Provider Capabilities explains how Migaki stays provider-neutral without becoming provider-naive.
- Adapters and Backends describes how Migaki can integrate with frameworks, gateways, provider APIs, workflow engines, and trace systems.
- Examples contains concrete workflows that should drive early implementation.
- Benchmarks and Evaluation defines the measurement bar for claiming an optimization worked.
- Risks and Open Questions tracks design risks, ambiguous boundaries, and research questions.
- Glossary keeps project vocabulary stable.
Migaki is an execution optimizer for agentic systems: it represents model/tool/retrieval/context workflows as portable execution graphs, transforms them under explicit cost, latency, quality, and governance constraints, lowers them into provider-specific runtimes, and emits evidence traces for every optimization.