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Gemini

OrganizationPopular
softaworks
gemini

Use when the user asks to run Gemini CLI for code review, plan review, or big context (>200k) processing. Ideal for comprehensive analysis requiring large context windows. Uses Gemini 3 Pro by default for state-of-the-art reasoning and coding.

Overview

Publishersoftaworks
Repositoryagent-toolkit
Skill namegemini
Stars
2.5K
Forks
226
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by softaworks on GitHub. Read the source before you install it.

Installation

Install the Gemini AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/softaworks/agent-toolkit.git /tmp/agent-toolkit
mkdir -p .claude/skills
cp -r /tmp/agent-toolkit/skills/gemini .claude/skills/gemini
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gemini in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gemini on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gemini is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Gemini Skill Guide

When to Use Gemini

  • WHEN ASKED TO BE ACTIVATED
  • Code Review: Comprehensive code reviews across multiple files
  • Plan Review: Analyzing architectural plans, technical specifications, or project roadmaps
  • Big Context Processing: Tasks requiring >200k tokens of context (entire codebases, documentation sets)
  • Multi-file Analysis: Understanding relationships and patterns across many files

⚠️ Critical: Background/Non-Interactive Mode Warning

NEVER use --approval-mode default in background or non-interactive shells (like Claude Code tool calls). It will hang indefinitely waiting for approval prompts that cannot be provided.

For automated/background reviews:

  • ✅ Use --approval-mode yolo for fully automated execution
  • ✅ OR wrap with timeout: timeout 300 gemini ...
  • ❌ NEVER use --approval-mode default without interactive terminal

Symptoms of hung Gemini:

  • Process running 20+ minutes with 0% CPU usage
  • No network activity
  • Process state shows 'S' (sleeping)

Fix hung process:

bash
# Check if hung
ps aux | grep gemini | grep -v grep

# Kill if necessary
pkill -9 -f "gemini.*gemini-3-pro-preview"

Running a Task

  1. Ask the user (via AskUserQuestion) which model to use in a single prompt. Available models:

    • gemini-3-pro-preview ⭐ (flagship model, best for coding & complex reasoning, 35% better at software engineering than 2.5 Pro)
    • gemini-3-flash (sub-second latency, distilled from 3 Pro, best for speed-critical tasks)
    • gemini-2.5-pro (legacy option, strong all-around performance)
    • gemini-2.5-flash (legacy option, cost-efficient with thinking capabilities)
    • gemini-2.5-flash-lite (legacy option, fastest processing)
  2. Select the approval mode based on the task:

    • default: Prompt for approval (⚠️ ONLY for interactive terminal sessions)
    • auto_edit: Auto-approve edit tools only (for code reviews with suggestions)
    • yolo: Auto-approve all tools (✅ REQUIRED for background/automated tasks)
  3. Assemble the command with appropriate options:

    • -m, --model <MODEL> - Model selection
    • --approval-mode <default|auto_edit|yolo> - Control tool approval
    • -y, --yolo - Alternative to --approval-mode yolo
    • -i, --prompt-interactive "prompt" - Execute prompt and continue interactively
    • --include-directories <DIR> - Additional directories to include in workspace
    • -s, --sandbox - Run in sandbox mode for isolation
  4. For background/automated tasks, ALWAYS use --approval-mode yolo or add timeout wrapper. NEVER use default in non-interactive shells.

  5. Run the command and capture the output. For background/automated mode:

    bash
    # Recommended: Use yolo for background tasks
    gemini -m gemini-3-pro-preview --approval-mode yolo "Review this codebase for security issues"
    
    # Or with timeout (5 min limit)
    timeout 300 gemini -m gemini-3-pro-preview --approval-mode yolo "Review this codebase"
  6. For interactive sessions with an initial prompt:

    bash
    gemini -m gemini-3-pro-preview -i "Review the authentication system" --approval-mode auto_edit
  7. After Gemini completes, inform the user: "The Gemini analysis is complete. You can start a new Gemini session for follow-up analysis or continue exploring the findings."

Quick Reference

Use caseApproval modeKey flags
Background code reviewyolo-m gemini-3-pro-preview --approval-mode yolo
Background analysisyolo-m gemini-3-pro-preview --approval-mode yolo
Background with timeoutyolotimeout 300 gemini -m gemini-3-pro-preview --approval-mode yolo
Interactive code reviewdefault-m gemini-3-pro-preview --approval-mode default (interactive terminal only)
Code review with auto-editsauto_edit-m gemini-3-pro-preview --approval-mode auto_edit
Automated refactoringyolo-m gemini-3-pro-preview --approval-mode yolo
Speed-critical backgroundyolo-m gemini-3-flash --approval-mode yolo
Cost-optimized backgroundyolo-m gemini-2.5-flash --approval-mode yolo
Multi-directory analysisyolo (if background)--include-directories <DIR1> --include-directories <DIR2>
Interactive with promptauto_edit or default-i "prompt" --approval-mode <mode>

Model Selection Guide

ModelBest forContext windowKey features
gemini-3-pro-previewFlagship model: Complex reasoning, coding, agentic tasks1M input / 64k outputVibe coding, 76.2% SWE-bench, $2-4/M input
gemini-3-flashSub-second latency, speed-critical applications1M input / 64k outputDistilled from 3 Pro, TPU-optimized
gemini-2.5-proLegacy: Strong all-around performance1M input / 65k outputThinking mode, mature stability
gemini-2.5-flashLegacy: Cost-efficient, high-volume tasks1M input / 65k outputBest price ($0.15/M), thinking mode
gemini-2.5-flash-liteLegacy: Fastest processing, high throughput1M input / 65k outputMaximum speed, minimal latency

Gemini 3 Advantages: 35% higher accuracy in software engineering, state-of-the-art on SWE-bench (76.2%), GPQA Diamond (91.9%), and WebDev Arena (1487 Elo). Knowledge cutoff: January 2025.

Coming Soon: gemini-3-deep-think for ultra-complex reasoning with enhanced thinking capabilities.

Common Use Cases

Code Review (Background/Automated)

bash
# For background execution (Claude Code, CI/CD, etc.)
gemini -m gemini-3-pro-preview --approval-mode yolo \
  "Perform a comprehensive code review focusing on:
   1. Security vulnerabilities
   2. Performance issues
   3. Code quality and maintainability
   4. Best practices violations"

# With timeout safety (5 minutes)
timeout 300 gemini -m gemini-3-pro-preview --approval-mode yolo \
  "Perform a comprehensive code review..."

Plan Review (Background/Automated)

bash
# For background execution
gemini -m gemini-3-pro-preview --approval-mode yolo \
  "Review this architectural plan for:
   1. Scalability concerns
   2. Missing components
   3. Integration challenges
   4. Alternative approaches"

Big Context Analysis (Background/Automated)

bash
# For background execution
gemini -m gemini-3-pro-preview --approval-mode yolo \
  "Analyze the entire codebase to understand:
   1. Overall architecture
   2. Key patterns and conventions
   3. Potential technical debt
   4. Refactoring opportunities"

Interactive Code Review (Terminal Only)

bash
# ONLY use default mode in interactive terminal
gemini -m gemini-3-pro-preview --approval-mode default \
  "Review the authentication flow for security issues"

Following Up

  • Gemini CLI sessions are typically one-shot or interactive. Unlike Codex, there's no built-in resume functionality.
  • For follow-up analysis, start a new Gemini session with context from previous findings.
  • When proposing follow-up actions, restate the chosen model and approval mode.
  • Use AskUserQuestion after each Gemini command to confirm next steps or gather clarifications.

Error Handling

  • Stop and report failures whenever gemini --version or a Gemini command exits non-zero.
  • Request direction before retrying failed commands.
  • Before using high-impact flags (--approval-mode yolo, -y, --sandbox), ask the user for permission using AskUserQuestion unless already granted.
  • When output includes warnings or partial results, summarize them and ask how to adjust using AskUserQuestion.

Troubleshooting Hung Gemini Processes

Detection

bash
# Check for hung processes
ps aux | grep -E "gemini.*gemini-3" | grep -v grep

# Look for these symptoms:
# - Process running 20+ minutes
# - CPU usage at 0%
# - Process state 'S' (sleeping)
# - No network connections

Diagnosis

bash
# Get detailed process info
ps -o pid,etime,pcpu,stat,command -p <PID>

# Check network activity
lsof -p <PID> 2>/dev/null | grep -E "(TCP|ESTABLISHED)" | wc -l
# If result is 0, process is hung

Resolution

bash
# Kill hung Gemini processes
pkill -9 -f "gemini.*gemini-3-pro-preview"

# Or kill specific PID
kill -9 <PID>

# Verify cleanup
ps aux | grep gemini | grep -v grep

Prevention

  • ALWAYS use --approval-mode yolo for background/automated tasks
  • Add timeout wrapper for safety: timeout 300 gemini ...
  • Never use --approval-mode default in non-interactive shells
  • Monitor first run with ps to ensure process completes

Tips for Large Context Processing

  1. Be specific: Provide clear, structured prompts for what to analyze
  2. Use include-directories: Explicitly specify all relevant directories
  3. Choose the right model:
    • Use gemini-3-pro-preview for complex reasoning, coding tasks, and maximum analysis quality (recommended default)
    • Use gemini-3-flash for speed-critical tasks requiring sub-second response times
    • Use gemini-2.5-flash for cost-optimized high-volume processing
  4. Leverage Gemini 3's strengths: 35% better at software engineering tasks, exceptional at agentic workflows and vibe coding
  5. Break down complex tasks: Even with large context, structured analysis is more effective
  6. Save findings: Ask Gemini to output structured reports that can be saved for reference

CLI Version

Requires Gemini CLI v0.16.0 or later for Gemini 3 model support. Check version: gemini --version

Frequently asked questions

What does the Gemini AI skill do?

Use when the user asks to run Gemini CLI for code review, plan review, or big context (>200k) processing. Ideal for comprehensive analysis requiring large context windows. Uses Gemini 3 Pro by default for state-of-the-art reasoning and coding.

Why use Gemini on TypingMind?

Because you install it once and use it with any model. Gemini is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gemini in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/softaworks/agent-toolkit/tree/main/skills/gemini. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gemini?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gemini?

As many as you like. As long as a model supports skills, you can use Gemini with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gemini AI skill free?

Yes. It is published on GitHub by softaworks under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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