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Replace negative-priming with positive framing and reduce output verbosity in identify step - #473

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Replace negative-priming with positive framing and reduce output verbosity in identify step#473
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fix/identify-positive-framing-and-concise

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Summary

  • Positive framing: Replace "Do NOT include 'Controls ... vs.', 'Weakness:'" with "Focus on cause-effect relationships and factual outcomes" in consequences field (both Lever and LeverCleaned)
  • Reduced output targets: consequences 2-4→2-3 sentences, options "full sentence"→"one sentence", review_lever trimmed to "1-2 sentences"
  • Helps gpt-oss-20b complete within 600s — identify step makes 3 LLM calls per plan, slow providers take 200-1000s per call

Supersedes #471 (same positive framing fix, but #471 lacked the output reduction needed for gpt-oss-20b).

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🤖 Generated with Claude Code

…osity
Replace "Do NOT include 'Controls ... vs.', 'Weakness:'" with positive
framing ("Focus on cause-effect relationships and factual outcomes").
Reduce output targets: consequences 2-4 → 2-3 sentences, options
"a full sentence" → "one sentence", review_lever trimmed to "1-2
sentences" without "See system prompt section 4 for examples". Helps
gpt-oss-20b (reasoning model) complete within 600s plan budget — the
identify step makes 3 LLM calls per plan, and slow providers can take
200-1000s per call.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Self-improve iteration — analysis 70

Verdict: CONDITIONAL

  • gpt-oss-20b: 0/5 (PR Replace negative-priming prohibition with positive framing in consequences field #471) → 3/5 (partial recovery, but baseline was 5/5)
  • Positive framing in place, no "Controls X vs Y" patterns
  • System prompt inconsistency (B1): field desc says "2-3 sentences" but system prompt still says "2-4" → haiku verbosity grew +13% (now 2.1x baseline)
  • Fabricated numbers regression: gpt-oss-20b inventing HK$2m/5m/10m figures. "cause-effect" framing may encourage inventing specifics.

Closing — will fix system prompt consistency and strengthen number-evidence constraint in next PR.

@neoneyeneoneye closed this Mar 31, 2026
neoneye added a commit that referenced this pull request Mar 31, 2026
…e constraint
Replace negative prohibition ("Do NOT include 'Controls ... vs.'") with
positive framing. Align all three length targets (field desc ×2, system
prompt) to "2-3 sentences" — PR #473 only updated field descriptions,
leaving system prompt at "2-4" which haiku followed instead.
Strengthen number-evidence constraint: "Never invent percentages, costs,
or timeframes — only cite numbers that appear in the project context."
Placed before the cause-effect directive to prevent models from
fabricating specifics to satisfy cause-effect framing.
Reduce options to "one sentence" and review_lever to "1-2 sentences"
for conciseness, helping gpt-oss-20b stay within 600s plan budget.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
@neoneye
neoneye deleted the fix/identify-positive-framing-and-concise branch April 1, 2026 23:06
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