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chore(board): PROMPTS_VS_PRS ledger — 41 scoped briefs#213

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AdaWorldAPI merged 1 commit into
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claude/organize-bookkeeping-docs-PAxTU
Apr 19, 2026
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chore(board): PROMPTS_VS_PRS ledger — 41 scoped briefs#213
AdaWorldAPI merged 1 commit into
mainfrom
claude/organize-bookkeeping-docs-PAxTU

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Summary

Adds .claude/board/PROMPTS_VS_PRS.md — a bookkeeping ledger pairing each scoped brief in .claude/prompts/ (41 total) with its matching merged PR.

Test plan

  • wc -l .claude/board/PROMPTS_VS_PRS.md returns 41
  • Spot-check a few entries match the referenced PR titles

https://claude.ai/code/session_01AjKhV6bDne3ALQUPqt3ZsJ

…ed PRs

Bookkeeping ledger pairing each prompt brief in .claude/prompts/ with its
matching PR (by filename keyword). 16 mapped to merged PRs #176-#210; 25
marked `none` where no keyword match existed.
@AdaWorldAPI AdaWorldAPI merged commit 2a71926 into main Apr 19, 2026
AdaWorldAPI pushed a commit that referenced this pull request Apr 19, 2026
Append FINDING to EPIPHANIES.md. PR #213 + ndarray PR #110 demonstrated
the dumb-bookkeeper pattern: ~90 seconds, Haiku, enumerate+match+append.
Result is a grep-addressable index of every shipped artifact keyed by
the prompt-file brief that birthed it.

For every future "what did we ship about X" query the ledger replaces
a full-codebase grep with a single line — ~25 tokens vs ~25M tokens.
Seven orders of magnitude cheaper.

https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh
AdaWorldAPI pushed a commit that referenced this pull request Apr 19, 2026
Concrete three-pass recipe added to the cca2a skill:

  Pass 1 — Haiku bookkeeper (~90 s, mechanical): enumerate prompt files,
           match against git log, append one ledger line per pair.
  Pass 2 — Opus meta-synthesizer (read-only inputs): annotate the "none"
           rows from Pass 1 with superseded/open/stale classification.
  Pass 3 — Main thread consumer (sub-second per query): grep the ledger
           for every "what's open / shipped / about X" question.

Closes three token-waste channels simultaneously:
  - cold-start (20-30 turns → 3-5 turns)
  - find-code (~25M tokens → ~25 tokens, 10⁷×)
  - ambient arc knowledge (30-50% → 0%)

First deployments:
  - PR #213 (lance-graph, 41 prompts mapped, 90 s)
  - PR #110 (ndarray, 25 prompts mapped, 90 s)

Linked from SKILL.md under "What to read when".

https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh
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