--- title: "LLMDebugger vs self-repair" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/floridsleeves-llmdebugger-vs-theoxo-self-repair" tools: ["floridsleeves-llmdebugger", "theoxo-self-repair"] --- # LLMDebugger vs self-repair *GraphCanon updated Oct 7, 2026* ## Verdict Pick LLMDebugger if lLMDebugger offers step-by-step verification of runtime execution for large language models; pick self-repair if self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques. [LLMDebugger](https://github.com/FloridSleeves/LLMDebugger) reports 585 GitHub stars, 57 forks, and 5 open issues, last pushed Sep 10, 2024. [self-repair](https://github.com/theoxo/self-repair) has 15 stars, 3 forks, and 1 open issues, last pushed May 2, 2024. Figures are from public GitHub metadata via [LLMDebugger's repository](https://github.com/FloridSleeves/LLMDebugger) and [self-repair's repository](https://github.com/theoxo/self-repair). | | [LLMDebugger](/tools/floridsleeves-llmdebugger.md) | [self-repair](/tools/theoxo-self-repair.md) | | --- | --- | --- | | Tagline | A Large Language Model Debugger verifying runtime execution step by step | Supports research on self-repair mechanisms for code generation | | Stars | 585 | 15 | | Forks | 57 | 3 | | Open issues | 5 | 1 | | Language | Python | Python | | Adopt for | LLMDebugger offers step-by-step verification of runtime execution for large language models. | Self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques. | | Persona | - | - | | Runtime | - | - | | License | The LLMDebugger is distributed under the Apache-2.0 license. | - | | Categories | Developer Tools, Evaluation & Observability | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLMDebugger](/tools/floridsleeves-llmdebugger.md) | [self-repair](/tools/theoxo-self-repair.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 756d | 887d | | Archived on GitHub | No | Yes | | Open issues (now) | 5 | 1 | | Stars delta | +1 (30d) | 0 (30d) | | Full report | [trust report](/tools/floridsleeves-llmdebugger/trust.md) | [trust report](/tools/theoxo-self-repair/trust.md) | ## Shared compatibility - **Python**: [LLMDebugger](/tools/floridsleeves-llmdebugger.md) - Python runtime; [self-repair](/tools/theoxo-self-repair.md) - Python runtime ## Decision facts: LLMDebugger - **Pricing:** freemium - Free for use, based on its open-source nature with an Apache-2.0 license. - **Adopt for:** LLMDebugger offers step-by-step verification of runtime execution for large language models. - **License detail:** The LLMDebugger is distributed under the Apache-2.0 license. ## Decision facts: self-repair - **Adopt for:** Self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques. ## Choose when ### Choose LLMDebugger if… - Pricing: Free for use, based on its open-source nature with an Apache-2.0 license.. - Tags unique to LLMDebugger: acl'24, llm debugging, python debugger for ai, runtime verification. - Also covers Evaluation & Observability. - When detailed step-by-step inspection of the runtime behavior of large language models is required, LLMDebugger can provide precise insights into each execution phase. ### Choose self-repair if… - Tags unique to self-repair: code-repair, experiments replication, python, research-tools. - When aiming to replicate specific experimental data from the ICLR 2024 paper on self-repair in code generation - Leaner open-issue backlog (1). ## When NOT to use LLMDebugger - Avoid using if you are only interested in higher-level performance metrics rather than the intricate details of runtime behavior, as LLMDebugger emphasizes step-by-step execution. - Not recommended for teams lacking experience with Python or specific to this tool's installation and usage workflow that involves setting up a Conda environment. ## When NOT to use self-repair - For creating entirely new datasets or conducting large-scale human studies, as this repository focuses on replicating existing experiments - When the internal dependencies or incomplete code functions such as exec_sample in APPS are critical for your application without modification ## Common questions ### What is the difference between LLMDebugger and self-repair? LLMDebugger: A Large Language Model Debugger verifying runtime execution step by step. self-repair: Supports research on self-repair mechanisms for code generation. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLMDebugger over self-repair? Choose LLMDebugger over self-repair when Pricing: Free for use, based on its open-source nature with an Apache-2.0 license.; Tags unique to LLMDebugger: acl'24, llm debugging, python debugger for ai, runtime verification; Also covers Evaluation & Observability; When detailed step-by-step inspection of the runtime behavior of large language models is required, LLMDebugger can provide precise insights into each execution phase. ### When should I choose self-repair over LLMDebugger? Choose self-repair over LLMDebugger when Tags unique to self-repair: code-repair, experiments replication, python, research-tools; When aiming to replicate specific experimental data from the ICLR 2024 paper on self-repair in code generation; Leaner open-issue backlog (1). ### When should I avoid LLMDebugger? Avoid using if you are only interested in higher-level performance metrics rather than the intricate details of runtime behavior, as LLMDebugger emphasizes step-by-step execution. Not recommended for teams lacking experience with Python or specific to this tool's installation and usage workflow that involves setting up a Conda environment. ### When should I avoid self-repair? For creating entirely new datasets or conducting large-scale human studies, as this repository focuses on replicating existing experiments When the internal dependencies or incomplete code functions such as exec_sample in APPS are critical for your application without modification ### Is LLMDebugger or self-repair more popular on GitHub? LLMDebugger has more GitHub stars (585 vs 15). Stars measure visibility, not whether either tool fits your constraints. ### Are LLMDebugger and self-repair open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LLMDebugger or self-repair? GraphCanon lists graph-backed alternatives at [LLMDebugger alternatives](/tools/floridsleeves-llmdebugger/alternatives) and [self-repair alternatives](/tools/theoxo-self-repair/alternatives) ([LLMDebugger markdown twin](/tools/floridsleeves-llmdebugger/alternatives.md), [self-repair markdown twin](/tools/theoxo-self-repair/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/floridsleeves-llmdebugger-vs-theoxo-self-repair.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLMDebugger or self-repair? LLMDebugger: Dormant. self-repair: Archived. 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 LLMDebugger and self-repair? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLMDebugger trust report](/tools/floridsleeves-llmdebugger/trust); [self-repair trust report](/tools/theoxo-self-repair/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=floridsleeves-llmdebugger`](/api/graphcanon/graph?tool=floridsleeves-llmdebugger) - 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/_