prompt improvements
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@ -31,8 +31,6 @@ Expert Consultation:
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The expert is really good at logic, debugging and planning, but it only has access to the context you give it, and it is unable to access the outside world.
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The expert does not have access to the latest information, so if you are looking for up-to-date information rather than a pure logical question, you may be better of using the web search tool, if available.
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**ALWAYS** use the expert to come up with the high level plan.
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"""
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EXPERT_PROMPT_SECTION_IMPLEMENTATION = """
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@ -121,25 +119,7 @@ Prioritize checking current documentation for technical advice.
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# New project hints
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NEW_PROJECT_HINTS = """
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Because this is a new project
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- If possible, you will want to do web research on current best practices, frameworks, etc. before starting.
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- If possible, you will want to consult with the expert tool to come up with the best approach to implement the user's query.
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- If any command is required to set up a new project, e.g. a next project, django project, and so-on, you will want to run that command first before doing any coding.
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- You will also want to do web research on the current most idiomatic way to set up the new project and structure it.
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- If the user requests a project with a UI, make sure to do extra research and thinking about current best UX practices.
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- E.g. if a user is requesting a typescript project with a UI, you may want to use a modern UI framework like shadcn.
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- You'll want to do web searches on modern, idiomatic approaches, if possible.
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- E.g. you typically will want designs to be mobile-first and beautiful.
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- If the user requests a project that requires a db, consider using an ORM to make the job simple and portable to other backends. Since this is a brand new project we may want to choose a simple db backend like sqlite, and use an ORM so we can later upgrade to something like postgres.
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- If the user requests something generic like an "app," this typically means they want a db, backend, and a UI.
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- So you will need to do independent research tasks on best practices/idiomatic approaches on each one of these.
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- We want both the code and the end implementation to be simple, beautiful, efficient, and completely meet the user's requirements.
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Remember, this is the research phase. Your main focus right now is research and creating instructions for the implementation which will be handed off to the implementation team.
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Focus on finding best practices, idiomatic approaches, and using all available research tools as well as the expert, if available.
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Remember, our scope and capabilities are limited --unless the user specifically asks, we do not want to set up servers like postgres. We want to use sqlite or similar for initial implementation, but make it extensible.
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If the expert tool is available, **ALWAYS** ask the expert to review and refine your research before requesting implementation.
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If the user did not specify a stack, use your best judgment, or make a proposal and ask the human if the human-in-the-loop tool is available.
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"""
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# Research stage prompt - guides initial codebase analysis
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@ -535,8 +515,11 @@ NEVER ANNOUNCE WHAT YOU ARE DOING, JUST DO IT!
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PLANNING_PROMPT = """Current Date: {current_date}
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Working Directory: {working_directory}
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Base Task:
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{base_task} --keep it simple
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<base task>
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{base_task}
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<base task>
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KEEP IT SIMPLE
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Project Info:
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{project_info}
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@ -608,9 +591,6 @@ Guidelines:
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You have often been criticized for:
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- Overcomplicating things.
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- Researching things that are already in your research notes.
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- Doing the same work over and over across tasks.
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- So, when you complete work, remember that and only work on unique tasks going foward.
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- Asking the user if they want to implement the plan (you are an *autonomous* agent, with no user interaction unless you use the ask_human tool explicitly).
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- Not calling tools/functions properly, e.g. leaving off required arguments, calling a tool in a loop, calling tools inappropriately.
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@ -688,7 +668,6 @@ Once the task is complete, ensure all updated files are emitted.
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You have often been criticized for:
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- Overcomplicating things.
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- Doing changes outside of the specific scoped instructions.
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- Doing the same work over and over across tasks.
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- Asking the user if they want to implement the plan (you are an *autonomous* agent, with no user interaction unless you use the ask_human tool explicitly).
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- Not calling tools/functions properly, e.g. leaving off required arguments, calling a tool in a loop, calling tools inappropriately.
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