gpt-prompt-architect

Design system prompts for GPT-5 by applying CTCO-based patterns to Codex AGENTS.md and ChatGPT Custom Instructions, ensuring compaction-aware architecture and memory-handling patterns for robust, scalable performance across surfaces.

GPT prompt failure modes like drift and tool-spamming are mitigated by auditing prompts against established failure patterns, applying compaction-aware design, and migrating procedural content from high-volume files into skills for on-demand guidance.

Structure an AGENTS.md file to prevent prompt drift by codifying CTCO-based design patterns, implementing memory-handling protocols, and migrating procedural content into skills for compact, on-demand guidance.

Migrate procedural content from high-volume prompt files into skills when compaction risks degrade performance, ensuring compact, on-demand guidance that reduces drift and tool-spamming risks across GPT-5 surfaces.

You can use the same prompt engineering framework for ChatGPT Custom Instructions and Codex CLI by applying CTCO patterns and compaction-aware design to standardize and harden prompt workflows across both surfaces.

GPT prompts cause tool-spamming due to unmanaged procedural content and missing compaction-aware design; audit them by checking against established failure patterns and migrating high-volume content into on-demand skills.