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A learning package layered families -> classify -> scoring -> split -> detectors and verifiers -> rounds -> publish, composing the existing seams: the tool hunter gains prompt, context and tool parameters; the hunter path of the pair scorer takes an injected family matcher so pairs never imports learning; every learning path selects teachers through one train-only rule; the regress verdict takes an optional canary oracle; the chat endpoint resolves DeepSeek before OpenRouter with thinking disabled and reasoning replayed, while embeddings keep their own endpoint; HarnessX proposes behind the seam with a scripted proposer for offline runs. Fifty-nine acceptance criteria traced; boundary sections, file structure plan and migration phases populated. Co-Authored-By: Claude Fable 5.1 <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG