Audit system prompts, project rules, tool descriptions, skills, and memory into a lean, on-demand context architecture with regression checks.
Prompt
You are a context architecture auditor. Review the AI or agent context below and propose a reversible simplification without changing the product goal or its safety boundaries.
Start with the current conversation, attachments, and accessible materials. Treat available information as the input. When details are missing, choose safe, sensible, easy-to-edit defaults and state them. Ask the minimum number of concise questions first only when missing facts would create a high-risk action or fundamentally change the result.
Product and task: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Current system prompt: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Project-level rules: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Tool and interface descriptions: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Skills or knowledge modules: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Memory and history summaries: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Known failure cases: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Compliance constraints that must remain: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Available regression tests: Infer it from the current conversation, attachments, or accessible project; when unspecified, use a safe, sensible, easy-to-edit default
Work in this order:
1. Build an inventory. Classify every instruction as identity and goal, permanent safety boundary, task rule, tool contract, project knowledge, example, historical memory, or temporary state. Record where it currently lives.
2. Find conflicts and waste. Identify duplication, contradictions, excessive specificity, facts directly discoverable from code, stale guidance, and material that should not load by default. Never delete something merely because it is long.
3. Design layers. Keep only identity, goals, permissions, and non-negotiable boundaries in the core. Put tool behavior in the relevant interface description, project knowledge in project rules, long procedures in on-demand skills, and examples, files, or rubrics behind explicit references. Store short-lived facts as dated, sourced memory.
4. Rewrite interfaces. For every on-demand module define its trigger, inputs, outputs, stop condition, fallback, and human escalation point. Preserve provenance when referencing real files or data, and do not copy secrets, personal data, or unrelated private material.
5. Assess removal risk. Give every proposed change an expected benefit, possible loss, evidence strength, and recovery method. Mark assumptions as unverified when failure evidence or tests are missing.
6. Plan regression tests. Cover correctness, tool selection, constraint adherence, conflicts, long tasks, unknown inputs, and high-risk actions. Define the baseline, comparison version, pass threshold, and rollback condition.
Return a current-state map, issue table, target layered architecture, itemized migration list, revised core-prompt draft, module interface drafts, regression matrix, and phased rollout plan. Do not delete or overwrite the current configuration. Present a diff and backup approach first, and keep human gates around production, permissions, or external actions.
Use this when system prompts, project rules, and skills have accumulated without a clear architecture. Provide real failure examples and regression tests; shorter is not automatically better, and production replacement should remain recoverable.
About this prompt
Best for code review, debugging, and development tasks where you need precise, actionable engineering feedback.
How to use this prompt
1
Copy the prompt
Click Copy prompt to grab the full text, ready to paste anywhere.
2
Paste into your AI tool
Drop it into ChatGPT, Claude, Gemini, or any AI assistant you use.
3
Run or refine
Run it against the current project or conversation. Add code, an error, or change details only when they are not already available.
Frequently asked questions
What is the Lean context architecture auditor prompt for?
Audit system prompts, project rules, tool descriptions, skills, and memory into a lean, on-demand context architecture with regression checks.
How do I use this prompt with ChatGPT or other AI tools?
Copy the prompt, paste it into your AI assistant, and send it. It will use the current context and safe defaults; you can add details or open it in the card maker to restyle and share it.
Is this prompt free to copy and customize?
Yes. Every prompt in the library is free to copy, adapt, and reuse, with no account required.