Sprint 003 findings + Sprint 004 pipeline decision audit plan
- split_prereq_op_dataset.py: extract accepted/rejected/schema-drift rows per gate - gen_prereq_op_rsa_data.py: convert accepted rows to Fabricate TSV format - 1000-run extracted dataset: 1297 accepted prereq_op rows, 24 schema-drift - Key finding: needs_validate_intake always True; effective gate is binary (needs_resolve_dependencies 77%, needs_architect_review 20%) - Key finding: run corpus text is template-driven (17 unique inputs) — not suitable for text-based training; RSA exists before ideal input is available - ROADMAP: gate lifecycle framing — goal is choice of backend, not forced determinism; RSA operates on imperfect/mixed/incomplete input by design - training_data_strategy.md: taskitem-as-self-contained-work-unit constraint - SPRINT-003: updated with 1000-run results, text audit findings, design constraints - SPRINT-004: pipeline decision audit — manual walkthrough of every decision from project description to generated artifact; execute next session Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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semantic/prereq_op_dataset/accepted.ndjson
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semantic/prereq_op_dataset/accepted.ndjson
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