--- title: "DecryptPrompt vs awesome-claude-code" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dsxiangli-decryptprompt-vs-hesreallyhim-awesome-claude-code" tools: ["dsxiangli-decryptprompt", "hesreallyhim-awesome-claude-code"] --- # DecryptPrompt vs awesome-claude-code *GraphCanon updated Aug 16, 2026* ## Verdict Pick DecryptPrompt if decryptPrompt is an open-source repository that summarizes prompt and large language model research papers while offering related datasets and models for AI content generation facilitation; pick awesome-claude-code if awesome-claude-code is a curated collection of resources for Claude Code, an AI coding companion from Anthropic PBC, aimed at optimizing workflows and providing high-quality developer tooling. [DecryptPrompt](https://github.com/DSXiangLi/DecryptPrompt) reports 3.4k GitHub stars, 320 forks, and 1 open issues, last pushed May 6, 2026. [awesome-claude-code](https://github.com/hesreallyhim/awesome-claude-code) has 52k stars, 4.6k forks, and 861 open issues, last pushed Aug 16, 2026. Figures are from public GitHub metadata via [DecryptPrompt's repository](https://github.com/DSXiangLi/DecryptPrompt) and [awesome-claude-code's repository](https://github.com/hesreallyhim/awesome-claude-code). | | [DecryptPrompt](/tools/dsxiangli-decryptprompt.md) | [awesome-claude-code](/tools/hesreallyhim-awesome-claude-code.md) | | --- | --- | --- | | Tagline | Summarizes Prompt&LLM Papers, Open-source Data&Models, AIGC Applications | A curated collection of resources for Claude Code, an AI coding companion from Anthropic PBC. | | Stars | 3,427 | 52,394 | | Forks | 320 | 4,583 | | Open issues | 1 | 861 | | Language | - | Python | | Adopt for | DecryptPrompt is an open-source repository that summarizes prompt and large language model research papers while offering related datasets and models for AI content generation facilitation. | awesome-claude-code is a curated collection of resources for Claude Code, an AI coding companion from Anthropic PBC, aimed at optimizing workflows and providing high-quality developer tooling. | | Persona | - | - | | Runtime | - | - | | License | - | Other | | Categories | Developer Tools, Model Training | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DecryptPrompt](/tools/dsxiangli-decryptprompt.md) | [awesome-claude-code](/tools/hesreallyhim-awesome-claude-code.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 83d | 0d | | Open issues (now) | 1 | 861 | | Stars delta | Unknown | +2.2k (30d) | | Open issues delta | Unknown | +176 (30d) | | Full report | [trust report](/tools/dsxiangli-decryptprompt/trust.md) | [trust report](/tools/hesreallyhim-awesome-claude-code/trust.md) | ## Decision facts: DecryptPrompt - **Adopt for:** DecryptPrompt is an open-source repository that summarizes prompt and large language model research papers while offering related datasets and models for AI content generation facilitation. ## Decision facts: awesome-claude-code - **Adopt for:** awesome-claude-code is a curated collection of resources for Claude Code, an AI coding companion from Anthropic PBC, aimed at optimizing workflows and providing high-quality developer tooling. ## Choose when ### Choose DecryptPrompt if… - Tags unique to DecryptPrompt: aigc, chain-of-thought, chatgpt, demonstration. - Also covers Model Training. - When you need detailed summaries of prompt-engineering and LLM-related research, as DecryptPrompt is dedicated to this area. ### Choose awesome-claude-code if… - Tags unique to awesome-claude-code: agent-skills, agentic-code, ai-workflow-optimization, anthropic-claude. - Also covers AI Agents. - - When you require comprehensive resource lists specifically for integrating Claude Code into your development workflow. ## When NOT to use DecryptPrompt - Avoid using DecryptPrompt if you require a solution that supports languages other than English effectively, as the repository's descriptions are in Chinese. - If your development needs go beyond summarization and data/model provision into complex coding examples or comprehensive API documentation, DecryptPrompt might not satisfy these requirements. ## When NOT to use awesome-claude-code - - For general AI-agent resources that do not align with the specific functionalities or integrations provided by Anthropic PBC's Claude Code. - - When you prefer a more generalized approach without specialized focus on Anthropic PBC’s AI coding companion. ## Common questions ### What is the difference between DecryptPrompt and awesome-claude-code? DecryptPrompt: Summarizes Prompt&LLM Papers, Open-source Data&Models, AIGC Applications. awesome-claude-code: A curated collection of resources for Claude Code, an AI coding companion from Anthropic PBC.. See the comparison table for live GitHub stats and shared categories. ### When should I choose DecryptPrompt over awesome-claude-code? Choose DecryptPrompt over awesome-claude-code when Tags unique to DecryptPrompt: aigc, chain-of-thought, chatgpt, demonstration; Also covers Model Training; When you need detailed summaries of prompt-engineering and LLM-related research, as DecryptPrompt is dedicated to this area. ### When should I choose awesome-claude-code over DecryptPrompt? Choose awesome-claude-code over DecryptPrompt when Tags unique to awesome-claude-code: agent-skills, agentic-code, ai-workflow-optimization, anthropic-claude; Also covers AI Agents; - When you require comprehensive resource lists specifically for integrating Claude Code into your development workflow. ### When should I avoid DecryptPrompt? Avoid using DecryptPrompt if you require a solution that supports languages other than English effectively, as the repository's descriptions are in Chinese. If your development needs go beyond summarization and data/model provision into complex coding examples or comprehensive API documentation, DecryptPrompt might not satisfy these requirements. ### When should I avoid awesome-claude-code? - For general AI-agent resources that do not align with the specific functionalities or integrations provided by Anthropic PBC's Claude Code. - When you prefer a more generalized approach without specialized focus on Anthropic PBC’s AI coding companion. ### Is DecryptPrompt or awesome-claude-code more popular on GitHub? awesome-claude-code has more GitHub stars (52,394 vs 3,427). Stars measure visibility, not whether either tool fits your constraints. ### Are DecryptPrompt and awesome-claude-code open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to DecryptPrompt or awesome-claude-code? GraphCanon lists graph-backed alternatives at [DecryptPrompt alternatives](/tools/dsxiangli-decryptprompt/alternatives) and [awesome-claude-code alternatives](/tools/hesreallyhim-awesome-claude-code/alternatives) ([DecryptPrompt markdown twin](/tools/dsxiangli-decryptprompt/alternatives.md), [awesome-claude-code markdown twin](/tools/hesreallyhim-awesome-claude-code/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/dsxiangli-decryptprompt-vs-hesreallyhim-awesome-claude-code.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DecryptPrompt or awesome-claude-code? DecryptPrompt: Steady. awesome-claude-code: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for DecryptPrompt and awesome-claude-code? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DecryptPrompt trust report](/tools/dsxiangli-decryptprompt/trust); [awesome-claude-code trust report](/tools/hesreallyhim-awesome-claude-code/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dsxiangli-decryptprompt`](/api/graphcanon/graph?tool=dsxiangli-decryptprompt) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_