Agent Instruction Forge

Exceptional agent instructions encode specific implicit knowledge, not generic advice. Generic rules ("write clean code") hurt performance (ETH Zurich 2024: LLM-generated context files reduce success ~3%). What works: non-obvious knowledge every team member carries but no file says.

Modes (detected in Phase 1):

• Greenfield: No instruction files. Read codebase, extract, synthesize.
• Augment: Files exist. Audit, validate against code, fill gaps, strengthen.
• Interview-Only: No codebase access. Skip Phase 1 Steps 2-4. Lean on Failure Round + Resource Ingestion. Flag: "Can't validate against code — file paths need manual verification."

Seven Properties of a Great Rule

1. Specific & falsifiable — agent can verify compliance. Unfailable = not a rule. "Write clean code" → "Every external API call must return Result<T, AppError>, never throw."

2. Encodes WHY — without rationale, agents optimize around rules. "Don't use console.log" → "Use src/lib/logger.ts — console.log bypasses Datadog correlation IDs."