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opencode-gemiterm-skills

Gemini terminal skills for AI agents — chat export, search & AI-powered debates

OpenCode Plugin npm version MIT License

Quick Start · Skills · Examples · Requirements · Contributing


Bring the power of Google Gemini directly into your AI agent sessions. This package bundles two skills — gemiterm and debate-with-gemini — so any compatible agent can search your Gemini chats, export conversation history, and run structured multi-turn debates with Gemini to validate ideas before you commit to code.

Works with OpenCode, and any agent that supports the skill tool or can invoke CLI-installed skills via bunx/npx.

Bundled skills

Skill What it does
gemiterm Search, list, export, and manage your Google Gemini chat history from the terminal.
debate-with-gemini Run structured multi-turn technical debates with Gemini AI — perfect for validating architecture decisions, trade-offs, and design choices.

Both skills are loaded on demand. Metadata (name + description) is pre-loaded at session start; the full skill body loads only when the agent decides it's relevant — zero overhead when not in use.

Quick start

# Install skills via bunx
bunx opencode-gemiterm-skills install [--scope global]

# Or with npx
npx opencode-gemiterm-skills install [--scope global]

# Or skills.sh
npx skills add expert-vision-software/opencode-gemiterm-skills --skill [gemiterm/debate-with-gemini]

That's it — skills are available immediately.

Examples

🔍 Search and export Gemini chats

You: "Find my Gemini chats about React Server Components and export them."

Agent loads the gemiterm skill, searches your Gemini history, and exports matches:

Found 3 matching chats. Exported all to ./exports/ — here's a summary of each…

📦 Bulk export for offline analysis

You: "Export all my recent Gemini chats so I can grep through them."

Agent lists and exports chats in parallel:

Exported 18 chats to ./gemini-exports/ in Markdown. Search with: grep -r "topic" ./gemini-exports/

🗣️ Structured debate with Gemini

You: "Debate Gemini for/against using SQLite as the primary database for a SaaS app. Context: docs/arch.md. 5 turns."

Agent reads your context, seeds a new Gemini chat with the opposing stance, and runs 5 rounds of autonomous back-and-forth:

Debate complete (5 turns). Gemini argued FOR SQLite (simplicity, zero-config).
I argued AGAINST (concurrency limits, no network access, scaling ceiling).
Key agreements: fine for prototyping, migrate to Postgres before 100+ concurrent users.

🔄 Continue a previous debate

You: "Continue that SQLite debate for 3 more turns. Here's the chat_id: c_abc123."

Agent picks up exactly where the last round left off:

Resumed debate on chat c_abc123. Ran 3 additional turns.
Gemini conceded on the replication point but raised WAL-mode mitigations.

Requirements

Component Notes
gemiterm CLI Must be installed and authenticated. Both skills depend on it.
Google Account Required for gemini web. Expiring cookie is stored locally only.

Installation

CLI install (any agent)

# Via bunx
bunx opencode-gemiterm-skills install

# Via npx
npx opencode-gemiterm-skills install

OpenCode plugin

Add to your opencode.json:

{
  "plugins": ["opencode-gemiterm-skills"]
}

Why this plugin?

  • No context switching — access your Gemini conversations without leaving your agent.
  • Zero-config debates — let your agent argue both sides of a technical decision with real Gemini responses.
  • Portable chat data — export Gemini history to Markdown for grep, archival, or feeding into other tools.
  • Lightweight — pure skill bundle, no runtime dependencies, loads on demand.

Acknowledgments

  • OpenCode — plugin architecture and skill loader
  • gemiterm — underlying Gemini CLI

About

Skills for gemiterm cli that can access web gemini chats, continue them, and automate multi-agent collaboration.

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