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Pipeline Plan 211
Seth Ford edited this page Mar 9, 2026
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1 revision
Plan complete and saved to docs/plans/2026-03-09-memory-pattern-effectiveness-tracker.md.
Key discovery: The lib/memory-effectiveness.sh module (507 lines) already exists with core injection/outcome tracking, scoring, ranking, pruning, and reporting. The main work is enhancement + integration, not building from scratch.
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memeff_track_injection(),memeff_track_outcome(),memeff_score_pattern(),memeff_rank_patterns(),memeff_prune_ineffective(),memeff_proactive_score(),memeff_report() - 16 passing tests in
sw-memory-effectiveness-test.sh
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memeff_score_issue()— Pre-pipeline issue-to-pattern scoring (keyword overlap + label match + file overlap + effectiveness weighting, 0-100) -
Enhanced outcome tracking — Adds
pattern_injected,failure_occurred,failure_type_matched,failure_preventedfields - Enhanced reporting — Injection success rate, strategic export format, patterns-needing-refinement list
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Hook wiring — Connects
memeff_on_injectioninsw-loop.shandmemeff_on_pipeline_completeinpipeline-commands.sh+daemon-dispatch.sh -
CLI subcommands —
shipwright memory effectiveness [text|json|strategic]andshipwright memory score-issue - Integration tests — E2E flow tests for success/failure paths
- Full test suite validation — Regression check across pipeline, memory, and daemon tests
Two execution options:
1. Subagent-Driven (this session) — I dispatch fresh subagent per task, review between tasks, fast iteration
2. Parallel Session (separate) — Open new session with executing-plans, batch execution with checkpoints
Which approach?