Codebase context builder
Turn large repositories into clean prompt context without losing structure.
CodePiler gives you a controlled workspace for importing a repository, choosing the exact files that matter, and exporting AI-ready output in the format your workflow already uses.
Prompt workspace
Import, filter, select, export
Client-side
01
Upload project folder02
Review generated repository tree03
Select only relevant files04
Export text, JSON, XML, or MarkdownReadable context
Structure selected files into one prompt instead of pasting snippets manually.
Noise reduction
Filter oversized and irrelevant files before they ever clutter the prompt.
Ready to export
Switch output formats instantly and ship the result to any LLM workflow.
Built for focused prompt prep
The product is already a usable repository-to-prompt workspace.
The strongest part of CodePiler today is the core workflow: import code, inspect structure, control the selection set, and produce clean output fast.
Selective file control
Browse the repository tree and include exactly the files the prompt needs.
Format switching
Move between plain text, JSON, XML, and Markdown without rebuilding context.
Token awareness
Estimate prompt size before you send it to ChatGPT, Claude, or another model.
Local-first handling
Repository files stay in the browser workflow instead of being pushed to a backend.
Workflow
A simple pipeline for turning source code into LLM-ready context.
The UX should feel operational, not decorative. Each step strips away manual copying and keeps the context explicit.
01
Import repository files
Load a project folder directly in the browser and trim obvious noise up front.
02
Inspect the tree
Use the explorer to navigate folders, expand structure, and quickly control scope.
03
Generate final output
Preview the assembled prompt, verify token count, and copy or download the result.
Use cases
Built for developers who need cleaner context, not just a larger prompt.
The value is not only aggregation. It is choosing the right subset of the repository and preserving structure while doing it.
1
Explain unfamiliar codebases to an LLM without ad hoc copy-paste.
2
Prepare focused prompt context for debugging multi-file issues.
3
Package selected source files for documentation or onboarding prompts.
4
Assemble cleaner context when refactoring older repositories.
Ready to use
Open the workspace and generate structured context from your repository.
The current product already covers the core path. The next step is polishing the edges, not inventing the workflow.