[plan] Optimize Smoke Codex Token Usage

[github-actions]

Objective

Investigate and optimize the Smoke Codex workflow which consumed 15.9M tokens (43% of daily total) in a single run, reducing unnecessary token usage.

Context

From Discussion #14345, the Smoke Codex workflow consumed an extremely high number of tokens:

• Single run: 15.9M tokens
• Percentage of daily total: 43%
• Cost impact: Significant contribution to $6.02 daily spend

This suggests potential for optimization without compromising workflow quality.

Approach

1. Review Smoke Codex workflow definition and configuration
2. Analyze workflow run logs to understand token usage patterns:
   • What operations consume the most tokens?
   • Are there redundant API calls or data processing?
   • Is the AI agent context too large?
3. Identify optimization opportunities:
   • Reduce unnecessary context in prompts
   • Break large tasks into smaller, focused subtasks
   • Use selective file reading instead of full codebase scans
   • Implement caching for repeated operations
4. Implement optimizations while maintaining workflow quality
5. Test changes don't reduce workflow effectiveness

Files to Review

• .github/workflows/smoke-codex.md - Workflow definition
• Workflow run logs to analyze token usage patterns
• Related smoke test configurations

Acceptance Criteria

• Token usage analysis completed and documented
• Specific optimization opportunities identified
• Optimizations implemented (target: 50% reduction if feasible)
• Test run confirms reduced token usage
• Workflow quality maintained (all tests still pass)
• Cost impact documented (expected savings calculated)

AI generated by Plan Command for discussion #14345

• expires on Feb 9, 2026, 2:05 PM UTC

[github-actions]

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