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[FEATURE]: System prompt over specification audit and mitigation #16170

@micuintus

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@micuintus

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This is PR1 of #14398

Overspecification Hurts Performance

Two landmark studies prove that excessive specification in prompts degrades LLM performance:

Study Finding Evidence
Tang et al. (2025) Over-prompting degrades performance Performance peaks at 5-20 examples, then declines
Zi et al. (2025) More detail ≠ better code generation Excessive constraints create cognitive overload

Implication: Too few constraints → model ignores them. Too many → performance degrades.
Optimal: 5-7 high-impact constraints per category.

PR-1: Overspecification Audit & Reduction

Priority Score: 9.6/10 (HIGH impact, VERY HIGH evidence, LOW effort, ZERO overspec risk)

What: Audit all prompts and reduce constraints to 5-7 per category. Remove redundant instructions, verbose explanations, and duplicate content. Target <1500 tokens per prompt.

Why: Research proves excessive constraints degrade performance. Tang et al. (2025) found performance peaks at 5-20 examples then declines. Zi et al. (2025) confirmed excessive constraints create cognitive overload.

Evidence:

  • Tang et al. (2025): Performance peaks at 5-20 examples, then declines
  • Zi et al. (2025): Excessive constraints create cognitive overload
  • Chen et al. (2025): Promptware anti-patterns identified

Tasks:

  • Audit all prompt files in packages/opencode/src/session/prompt/*.txt
  • Count MUST/NEVER rules per category (target: ≤7)
  • Count examples per file (target: ≤5)
  • Measure token count per file (target: <1500)
  • Remove redundant/duplicate instructions
  • Create validation script scripts/audit-overspecification.ts
  • Add to CI pipeline

Files: packages/opencode/src/session/prompt/*.txt, scripts/audit-overspecification.ts

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coreAnything pertaining to core functionality of the application (opencode server stuff)discussionUsed for feature requests, proposals, ideas, etc. Open discussionperfIndicates a performance issue or need for optimization

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