Foundation: taxonomy, DeepSeek endpoint, corpus fields, TypeScript grammar,
curated hunter tools. Core: classifier tiers and measurement, per-pair family
scoring and aggregation, detector configurations and runner, verifier registry
with oracle callback, canary templates and second judge, journal and archive.
Integration: one teacher rule, family scoring on the pairs hunter path, round
zero with per-model noise floors, scan-path tags and manifest block, proposers,
acceptance and revert, round orchestration, publish, subcommands. Corpus
repairs and validation last. Both sanity reviews' findings recorded in the
plan; K-run evaluation honors requirement 3.5 at every stage.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
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
