--- title: "deepteam vs Auto-claude-code-research-in-sleep" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/confident-ai-deepteam-vs-wanshuiyin-auto-claude-code-research-in-sleep" tools: ["confident-ai-deepteam", "wanshuiyin-auto-claude-code-research-in-sleep"] --- # deepteam vs Auto-claude-code-research-in-sleep *GraphCanon updated Sep 20, 2026* ## Verdict Pick deepteam if deepTeam is a tool to assess security and safety in LLMs and AI agents through an implementation of guardrails; pick Auto-claude-code-research-in-sleep if auto-claude-code-research-in-sleep provides specialized Markdown-based utilities for automating and enhancing autonomous ML research by connecting various models in an open framework. [deepteam](https://trydeepteam.com) reports 2.8k GitHub stars, 449 forks, and 64 open issues, last pushed Aug 21, 2026. [Auto-claude-code-research-in-sleep](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep) has 16k stars, 1.4k forks, and 70 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [deepteam's repository](https://github.com/confident-ai/deepteam) and [Auto-claude-code-research-in-sleep's repository](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep). | | [deepteam](/tools/confident-ai-deepteam.md) | [Auto-claude-code-research-in-sleep](/tools/wanshuiyin-auto-claude-code-research-in-sleep.md) | | --- | --- | --- | | Tagline | Framework to red team LLMs and AI agents | Lightweight Markdown-only skills for autonomous ML research | | Stars | 2,789 | 16,383 | | Forks | 449 | 1,396 | | Open issues | 64 | 70 | | Language | Python | Python | | Adopt for | DeepTeam is a tool to assess security and safety in LLMs and AI agents through an implementation of guardrails. | Auto-claude-code-research-in-sleep provides specialized Markdown-based utilities for automating and enhancing autonomous ML research by connecting various models in an open framework. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT License, allowing for broad usage without restrictions on commercial use. | | Categories | Evaluation & Observability | AI Agents, Developer Tools, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deepteam](/tools/confident-ai-deepteam.md) | [Auto-claude-code-research-in-sleep](/tools/wanshuiyin-auto-claude-code-research-in-sleep.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 23d | 1d | | Open issues (now) | 64 | 70 | | Stars delta | +388 (30d) | +2.5k (30d) | | Open issues delta | +11 (30d) | +10 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/confident-ai-deepteam/trust.md) | [trust report](/tools/wanshuiyin-auto-claude-code-research-in-sleep/trust.md) | ## Decision facts: deepteam - **Pricing:** freemium - Free to use and modify under the terms of its Apache 2.0 license, encouraging community contribution and adaptation - **Requirements:** Min 4 GB RAM; Requires a Python environment.; No Docker required for operation. - **Adopt for:** DeepTeam is a tool to assess security and safety in LLMs and AI agents through an implementation of guardrails. ## Decision facts: Auto-claude-code-research-in-sleep - **Pricing:** freemium - Free to use under MIT license with no explicit pricing model indicated, though users might incur costs based on the AI models and services they choose to integrate. - **Requirements:** Compatibility with diverse language model agents without requiring lock-in or specific frameworks; Utilizes Markdown for skills, aiming at a lightweight automation layer on top of ML research tasks - **Adopt for:** Auto-claude-code-research-in-sleep provides specialized Markdown-based utilities for automating and enhancing autonomous ML research by connecting various models in an open framework. - **License detail:** MIT License, allowing for broad usage without restrictions on commercial use. ## Choose when ### Choose deepteam if… - License: deepteam is Apache-2.0, Auto-claude-code-research-in-sleep is MIT. - Pricing: Free to use and modify under the terms of its Apache 2.0 license, encouraging community contribution and adaptation. - Requirements: Min 4 GB RAM; Requires a Python environment.; No Docker required for operation.. - Tags unique to deepteam: apache 2.0, llm-guardrails, llm-red-teaming, llm-safety. - When you need a framework specifically designed for red-teaming large language models and AI agents under the Apache-2.0 license. ### Choose Auto-claude-code-research-in-sleep if… - License: Auto-claude-code-research-in-sleep is MIT, deepteam is Apache-2.0. - Pricing: Free to use under MIT license with no explicit pricing model indicated, though users might incur costs based on the AI models and services they choose to integrate.. - Requirements: Compatibility with diverse language model agents without requiring lock-in or specific frameworks; Utilizes Markdown for skills, aiming at a lightweight automation layer on top of ML research tasks. - Tags unique to Auto-claude-code-research-in-sleep: ai research, autonomous-agent, idea-generation, ml-research. - Also covers AI Agents, Developer Tools. - When you are looking to streamline idea discovery, experiment automation, and cross-model review loops specifically within the context of Python programming for machine learning research ## When NOT to use deepteam - If your team requires proprietary or more restrictive licensing conditions, given DeepTeam operates under an open-source Apache-2.0 license. - When you are working with non-Python programming environments as DeepTeam is only supported in Python. ## When NOT to use Auto-claude-code-research-in-sleep - If you require a solution that is tightly integrated with a specific AI development platform or requires the use of proprietary models - When your research workflow demands real-time data analysis and visualization tools that Auto-claude-code-research-in-sleep does not directly support ## Common questions ### What is the difference between deepteam and Auto-claude-code-research-in-sleep? deepteam: Framework to red team LLMs and AI agents. Auto-claude-code-research-in-sleep: Lightweight Markdown-only skills for autonomous ML research. See the comparison table for live GitHub stats and shared categories. ### When should I choose deepteam over Auto-claude-code-research-in-sleep? Choose deepteam over Auto-claude-code-research-in-sleep when License: deepteam is Apache-2.0, Auto-claude-code-research-in-sleep is MIT; Pricing: Free to use and modify under the terms of its Apache 2.0 license, encouraging community contribution and adaptation; Requirements: Min 4 GB RAM; Requires a Python environment.; No Docker required for operation.; Tags unique to deepteam: apache 2.0, llm-guardrails, llm-red-teaming, llm-safety; When you need a framework specifically designed for red-teaming large language models and AI agents under the Apache-2.0 license. ### When should I choose Auto-claude-code-research-in-sleep over deepteam? Choose Auto-claude-code-research-in-sleep over deepteam when License: Auto-claude-code-research-in-sleep is MIT, deepteam is Apache-2.0; Pricing: Free to use under MIT license with no explicit pricing model indicated, though users might incur costs based on the AI models and services they choose to integrate.; Requirements: Compatibility with diverse language model agents without requiring lock-in or specific frameworks; Utilizes Markdown for skills, aiming at a lightweight automation layer on top of ML research tasks; Tags unique to Auto-claude-code-research-in-sleep: ai research, autonomous-agent, idea-generation, ml-research; Also covers AI Agents, Developer Tools; When you are looking to streamline idea discovery, experiment automation, and cross-model review loops specifically within the context of Python programming for machine learning research. ### When should I avoid deepteam? If your team requires proprietary or more restrictive licensing conditions, given DeepTeam operates under an open-source Apache-2.0 license. When you are working with non-Python programming environments as DeepTeam is only supported in Python. ### When should I avoid Auto-claude-code-research-in-sleep? If you require a solution that is tightly integrated with a specific AI development platform or requires the use of proprietary models When your research workflow demands real-time data analysis and visualization tools that Auto-claude-code-research-in-sleep does not directly support ### Is deepteam or Auto-claude-code-research-in-sleep more popular on GitHub? Auto-claude-code-research-in-sleep has more GitHub stars (16,383 vs 2,789). Stars measure visibility, not whether either tool fits your constraints. ### Are deepteam and Auto-claude-code-research-in-sleep open source? Yes - both are open-source projects on GitHub (deepteam: Apache-2.0, Auto-claude-code-research-in-sleep: MIT). ### Where can I find alternatives to deepteam or Auto-claude-code-research-in-sleep? GraphCanon lists graph-backed alternatives at [deepteam alternatives](/tools/confident-ai-deepteam/alternatives) and [Auto-claude-code-research-in-sleep alternatives](/tools/wanshuiyin-auto-claude-code-research-in-sleep/alternatives) ([deepteam markdown twin](/tools/confident-ai-deepteam/alternatives.md), [Auto-claude-code-research-in-sleep markdown twin](/tools/wanshuiyin-auto-claude-code-research-in-sleep/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/confident-ai-deepteam-vs-wanshuiyin-auto-claude-code-research-in-sleep.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deepteam or Auto-claude-code-research-in-sleep? deepteam: Active. Auto-claude-code-research-in-sleep: 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 deepteam and Auto-claude-code-research-in-sleep? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deepteam trust report](/tools/confident-ai-deepteam/trust); [Auto-claude-code-research-in-sleep trust report](/tools/wanshuiyin-auto-claude-code-research-in-sleep/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=confident-ai-deepteam`](/api/graphcanon/graph?tool=confident-ai-deepteam) - 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/_