Dev toolsCAN I VIBECODE
Pieces?
BUILD FIRST
- One defined user and a repeatable end-to-end job
- A small, clear data model with sign-in only if it is genuinely needed
- Loading, empty, error, and success states that make the workflow feel complete
LEAVE FOR LATER
- Large integration marketplaces
- Multi-region scale and enterprise administration
- Every power-user setting from the established product
RESEARCH NOTES
What this tool actually does.
Pieces (pieces.app) is an AI memory layer for developers. Pieces OS runs locally to capture, enrich, and store code snippets and context. Its Copilot answers questions about selected code, with per-snippet saved conversations and suggested follow-up questions. Quick actions on returned code include Save to Snippet Repo, Share via link, Annotate Code, Find Similar, Tell Me More, Repair & Tidy, and Related Links/Tags. Snippets are browsable via Gallery/List views. The VS Code plugin adds 'Ask Copilot About Selection', pasting code blocks into chat, and extracting code from screenshots. An MCP server exposes history to Claude, Cursor, Codex, and Antigravity. Other capabilities include long-term memory, code suggestions/edits, and implementation context.
RESEARCHED BUILD PROMPT
Give this to your coding agent.
Build 'SnippetBrain', a local-first dev tool recreating the core Pieces workflow: automatic capture of copied code with surrounding file/IDE context, a searchable snippet repository (list/gallery views), and a snippet-aware chat assistant. Workflow: user copies code → app records snippet plus file path, language, and timestamp → user can edit tags or notes → in chat, user attaches a snippet or pastes code → assistant responds with that snippet as context and offers quick actions: annotate, explain, tidy, find similar. User-facing requirements: tray/background app, snippet history panel, fuzzy search, per-snippet chat threads with saved history, action buttons under returned code, OCR paste-from-screenshot import. Technical requirements: local SQLite store, language detection, tree-sitter for lightweight parsing, Electron or Tauri shell, clipboard monitoring plus an LSP-based editor bridge, chat via any OpenAI-compatible API with a system prompt for code tasks, local conversation storage. Implementation approach: Tauri + React front end, Rust backend for file watching and SQLite, secret ignore-list, streaming chat responses. Do not copy Pieces' brand, logo, UI layout, or marketing; use your own name and a simple two-pane design. Out of scope: multi-device sync, cloud accounts, MCP server, IDE marketplace distribution, team features. README must cover setup, API key config, how capture works, storage locations, privacy limits (nothing leaves the device except chat prompts), and limitations (no auto-upload, OCR accuracy, supported languages).