glebkudr/shotgun_code

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1999 stars · 231 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Shotgun is a desktop application that packages a local codebase into a structured context payload for LLMs, with AI-powered file selection and direct API execution against OpenAI, Gemini, and OpenRouter. It is built with a Go backend using the Wails framework and includes prompt templates, history tracking, and repo summaries.

Use cases

• package my codebase as context for an LLM
• stop copy-pasting files into Cursor manually
• let AI pick which files are relevant for a bug fix
• send a prompt directly to GPT-4o or Gemini with my repo context
• generate a full project context dump for AI reasoning
• keep a history of prompts and responses sent to LLMs
• create architecture summaries to ground LLM answers

When to choose

• you need to give an LLM large, structured context from a local repository
• you want AI-assisted selection of relevant files instead of manual picking
• you want to send prompts directly to OpenAI, Gemini, or OpenRouter from a desktop app
• you use tools like Cursor or Windsurf and need better context payloads

When to avoid

• you need a headless CLI or CI-integrated context generator
• your code cannot be sent to third-party LLM APIs
• you want an IDE plugin rather than a separate desktop application
• you need fine-grained code indexing or semantic search over the codebase

Facets

application · maturity active

llm-inference prompt-engineering developer-tools file-system developer-tools large-language-models cross-platform go llm-client codebase-context context-payload wails ai-coding-assistant openai gemini openrouter command-line desktop

Member repositories

For agents

markdown · JSON · MCP: product_card(name="glebkudr/shotgun_code")