tris203/precognition.nvim — 💭👀precognition.nvim - Precognition uses virtual text and gutter signs to show available motions.

Description and use

**Brief Summary (2‑3 sentences)**
*precognition.nvim* is a Neovim plugin that visualises possible motions with virtual text and gutter signs, giving you a “look‑ahead” view of where you can jump. Written in Lua, it has attracted a modest community (≈1.3 k stars) and is actively maintained as of May 2026. The plugin is positioned as a lightweight way to prototype AI‑enhanced editing features without building a model stack from scratch.

**Value**

• **Immediate UI feedback:** By overlaying motion hints directly in the editor, it speeds up navigation and reduces the cognitive load of remembering keybindings.
• **AI‑friendly entry point:** The visual hints can be driven by language‑model predictions (e.g., next‑token or code‑completion suggestions), letting teams experiment with AI‑augmented workflows (RAG, agents, etc.) without writing a full model integration.
• **Low barrier to try:** It ships as a standard Neovim plugin, so you can install it with any plugin manager and start seeing motion cues instantly.

**Practical Adoption Path**

1. **Install & evaluate** – Add tris203/precognition.nvim to your plugin manager (e.g., packer, lazy.nvim).
2. **Configure motion sources** – By default it uses built‑in Vim motions; to plug in AI predictions, map the virtual‑text provider to an LLM inference endpoint or a local code‑completion engine.
3. **Iterate in a sandbox** – Test the plugin in a personal or feature‑branch Neovim setup, confirming that the motion hints align with your AI model’s output.
4. **Integrate with existing tooling** – If the proof‑of‑concept is successful, embed the configuration into your shared Neovim config and document any required runtime dependencies (e.g., luajit, external LLM client).

**Production Readiness**

• **Maturity:** Medium. The plugin is actively maintained and has a solid star count, but its integration points (especially AI‑driven motion providers) are not documented in the metadata, so you’ll need to write custom glue code.
• **Risk considerations:** Verify the performance impact of generating virtual text on every keystroke, and ensure the external AI service you connect to has reliable latency and error handling.
• **Recommended use:** Ideal for prototypes, internal tooling, or teams that want to experiment with AI‑augmented editing. Before deploying to a larger user base, perform a dependency audit, add robust fallback behavior, and run a small‑scale user test to confirm the UI does not become noisy or distracting.

Problem

tris203/precognition.nvim helps add AI capability without starting from a blank model stack.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

💭👀precognition.nvim - Precognition uses virtual text and gutter signs to show available motions.

Source