--- title: "agentops vs auto-evaluator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-rlancemartin-auto-evaluator" tools: ["agentops-ai-agentops", "rlancemartin-auto-evaluator"] --- # agentops vs auto-evaluator *GraphCanon updated Aug 14, 2026* ## Verdict Pick agentops if agentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage; pick auto-evaluator if auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 612 forks, and 176 open issues, last pushed Jun 25, 2026. [auto-evaluator](https://autoevaluator.langchain.com/) has 1.1k stars, 92 forks, and 3 open issues, last pushed May 10, 2023. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [auto-evaluator's repository](https://github.com/rlancemartin/auto-evaluator). | | [agentops](/tools/agentops-ai-agentops.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | A lightweight evaluation tool for question-answering using Langchain | | Stars | 5,771 | 1,105 | | Forks | 612 | 92 | | Open issues | 176 | 3 | | Language | Python | Python | | Adopt for | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | Auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI. | | Persona | - | - | | Runtime | - | - | | License | MIT | - | | Categories | AI Agents, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 49d | 1186d | | Open issues (now) | 176 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/rlancemartin-auto-evaluator/trust.md) | ## Shared compatibility - **Python**: [agentops](/tools/agentops-ai-agentops.md) - Python runtime; [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) - Python runtime ## Decision facts: agentops - **Adopt for:** AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. ## Decision facts: auto-evaluator - **Adopt for:** Auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI. ## Choose when ### Choose agentops if… - Tags unique to agentops: ai-agents, benchmarking, cost-tracking. - Also covers AI Agents. - Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK ### Choose auto-evaluator if… - Tags unique to auto-evaluator: evaluation, gpt-3.5-turbo, langchain, llm. - Use when you need a lightweight solution for testing question-answering capabilities of Langchain models. - Leaner open-issue backlog (3). ## When NOT to use agentops - If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI - In case self-hosting of components is impractical due to resource constraints ## When NOT to use auto-evaluator - Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings. - If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature. ## Common questions ### What is the difference between agentops and auto-evaluator? agentops: Python SDK for AI agent monitoring and LLM cost tracking. auto-evaluator: A lightweight evaluation tool for question-answering using Langchain. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over auto-evaluator? Choose agentops over auto-evaluator when Tags unique to agentops: ai-agents, benchmarking, cost-tracking; Also covers AI Agents; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK. ### When should I choose auto-evaluator over agentops? Choose auto-evaluator over agentops when Tags unique to auto-evaluator: evaluation, gpt-3.5-turbo, langchain, llm; Use when you need a lightweight solution for testing question-answering capabilities of Langchain models; Leaner open-issue backlog (3). ### When should I avoid agentops? If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI In case self-hosting of components is impractical due to resource constraints ### When should I avoid auto-evaluator? Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings. If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature. ### Is agentops or auto-evaluator more popular on GitHub? agentops has more GitHub stars (5,771 vs 1,105). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and auto-evaluator open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to agentops or auto-evaluator? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [auto-evaluator alternatives](/tools/rlancemartin-auto-evaluator/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [auto-evaluator markdown twin](/tools/rlancemartin-auto-evaluator/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/agentops-ai-agentops-vs-rlancemartin-auto-evaluator.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or auto-evaluator? agentops: Steady. auto-evaluator: Dormant. 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 agentops and auto-evaluator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [auto-evaluator trust report](/tools/rlancemartin-auto-evaluator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentops-ai-agentops`](/api/graphcanon/graph?tool=agentops-ai-agentops) - 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/_