google-labs-code/jules-awesome-list

Some awesome prompts for Jules Agent

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google-labs-code/jules-awesome-list has 3k+ stars and 550+ forks on GitHub and was last pushed on Jun 30, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 31 minutes ago
Type:Curated List / Learning ResourceCategory(s):MCP Servers, Agent Skills & PromptsAI Coding AgentsAI Agents & LLM Apps
Added to GitGenius on September 21st, 2026
Created on May 17th, 2025
Open Issues & Pull Requests: 51 (+0)
GitHub issues: Enabled
Number of forks: 561
Total Stargazers: 3,188 (+1)
Total Subscribers: 81 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 59.6 days
Mean response time: 76.4 days
90th percentile: 173.9 days
Tracked items: 28

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Issue Activity (beta)

Open issues: 10
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 230 days
Stale 30+ days: 9
Stale 90+ days: 8

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Jules Awesome List is a curated collection of prompts designed for use with Jules Agent.

The collection addresses the need for high-quality, ready-to-use prompts that can be applied to Jules Agent workflows. Rather than requiring users to craft prompts from scratch, the repository provides pre-written examples that demonstrate effective ways to interact with the agent across different use cases and scenarios.

This resource suits developers who are adopting Jules Agent and want to accelerate their workflow by learning from established prompt patterns. It works well for teams exploring what Jules Agent can accomplish and seeking inspiration for their own prompt engineering. The collection serves as both a reference and a starting point for customization rather than a complete framework requiring extensive configuration.

The project shows active engagement with its user base through regular updates and refinements to the prompt collection. Contributions from the community indicate that the resource is being actively shaped by real-world usage patterns and feedback.