What kind of feature is this?
New CLI flag or option
What problem does this solve?
Currently, users must manually decide which files should be included in an AI context package.
This becomes difficult in medium or large repositories where a simple change request may involve multiple related files across frontend, backend, shared components, utilities, or configuration layers.
Example workflow today:
contextzip src/components/Login.tsx src/lib/toast.ts
The user has to manually discover and select relevant files before asking an AI model for help.
This creates friction in AI-assisted development workflows and often results in:
- missing context
- oversized context packages
- unnecessary token usage
- repeated retries with AI models
The problem becomes more noticeable when the requested change is described in natural language instead of explicit file paths.
Example:
contextzip --prompt "Change toast color on failed login"
The tool currently has no way to infer which files are likely related to the request.
Proposed solution
Introduce a new prompt-aware mode that uses lightweight AI-assisted relevance selection to automatically determine which files should be included in the generated context package.
Example usage:
contextzip --prompt "Change toast color on failed login"
Proposed workflow:
-
Scan the project structure
-
Build a lightweight project map using:
- file names
- directory structure
- optional import relationships
-
Send the project map and user prompt to a lightweight/local AI model
-
Receive a ranked list of likely relevant files
-
Automatically generate:
- context zip
- prompt.txt
- optional metadata
Example selected files:
app/login/page.tsx
components/ui/toast.tsx
lib/auth.ts
server/auth/login.ts
Initial implementation can remain intentionally simple:
- filename-based relevance matching
- directory semantics
- framework-aware heuristics
Future improvements may include:
- import graph analysis
- semantic embeddings
- git-aware weighting
- AST/symbol relationships
- local/offline model support
The goal is not to solve the coding task itself, but to intelligently reduce the amount of manual context selection required before sending code to ChatGPT, Claude, or other AI systems.
If this is a new framework — what should be excluded?
No response
What kind of feature is this?
New CLI flag or option
What problem does this solve?
Currently, users must manually decide which files should be included in an AI context package.
This becomes difficult in medium or large repositories where a simple change request may involve multiple related files across frontend, backend, shared components, utilities, or configuration layers.
Example workflow today:
The user has to manually discover and select relevant files before asking an AI model for help.
This creates friction in AI-assisted development workflows and often results in:
The problem becomes more noticeable when the requested change is described in natural language instead of explicit file paths.
Example:
contextzip --prompt "Change toast color on failed login"The tool currently has no way to infer which files are likely related to the request.
Proposed solution
Introduce a new prompt-aware mode that uses lightweight AI-assisted relevance selection to automatically determine which files should be included in the generated context package.
Example usage:
contextzip --prompt "Change toast color on failed login"Proposed workflow:
Scan the project structure
Build a lightweight project map using:
Send the project map and user prompt to a lightweight/local AI model
Receive a ranked list of likely relevant files
Automatically generate:
Example selected files:
Initial implementation can remain intentionally simple:
Future improvements may include:
The goal is not to solve the coding task itself, but to intelligently reduce the amount of manual context selection required before sending code to ChatGPT, Claude, or other AI systems.
If this is a new framework — what should be excluded?
No response