Four Fixes for GPT6-Astra Token Burn: Context Management Prompts, 2-5x Better Cost
alexcovo_eth · x · 2026-09-06
The author shares a hands-on playbook for cutting GPT6-Astra's token consumption:
- Enable experimental context management by setting experimentalmode = true under [features.contextmanagement] in /.codex/config.toml, so a single task can retain notes and retrieve past messages/tool results across context windows;
- Trim AGENTS.md and SKILL.md: merge duplicate rules, tighten trigger descriptions, and move long examples into reference files;
- Match reasoning effort to the task: medium/high for routine work, extra-high only for complex jobs — "Ultra" has almost no real use case;
- Stick to normal speed: measured task value-for-cost is 2-5x better than GPT5.6sol /fast, since Astra avoids noisy output and pointless test runs.
The post also includes two ready-to-use prompts you can paste into Codex: one to back up and idempotently edit the config (with TOML validation), and one to audit and optimize AGENTS.md files and enabled Skills.
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