Comparison
agent-opt vs llm_agents
Verdict
Pick agent-opt if agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies; pick llm_agents if llm_agents is a Python library enabling users to build simple agents directed by large language models, featuring functions like executing Python code and using Google search.
Markdown twin · agent-opt alternatives · llm_agents alternatives
GraphCanon updated Oct 3, 2026
9views this month
vs
Trust & integrity
| Signal | agent-opt | llm_agents |
|---|---|---|
| Maintenance | Archived (95d since push) As of Oct 3, 2026 · github_public_v1 | Dormant (453d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 3, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agent-opt
- Open Source Library for Automated Optimization of AI Agent Workflows
- llm_agents
- Library to build agents controlled by LLMs
Stars
- agent-opt
- 75
- llm_agents
- 1.1k
Forks
- agent-opt
- 9
- llm_agents
- 86
Open issues
- agent-opt
- 0
- llm_agents
- 4
Language
- agent-opt
- Python
- llm_agents
- Python
Adopt for
- agent-opt
- Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies.
- llm_agents
- llm_agents is a Python library enabling users to build simple agents directed by large language models, featuring functions like executing Python code and using Google search.
Persona
- agent-opt
- -
- llm_agents
- -
Runtime
- agent-opt
- -
- llm_agents
- -
License
- agent-opt
- Apache-2.0
- llm_agents
- MIT
Last pushed
- agent-opt
- Jun 30, 2026
- llm_agents
- Jun 23, 2025
Categories
- agent-opt
- AI Agents, Evaluation & Observability
- llm_agents
- AI Agents
Trust and health
Maintenance
- agent-opt
- Archived (8%)
- llm_agents
- Dormant (18%)
Days since push
- agent-opt
- 95d
- llm_agents
- 453d
Archived on GitHub
- agent-opt
- Yes
- llm_agents
- No
Open issues (now)
- agent-opt
- 0
- llm_agents
- 4
Stars delta
- agent-opt
- +4 (30d)
- llm_agents
- +1 (30d)
Open issues delta
- agent-opt
- 0 (30d)
- llm_agents
- +1 (30d)
Owner type
- agent-opt
- Organization
- llm_agents
- User
OSV dependency advisories
- agent-opt
- No lockfile (source not queried)
- llm_agents
- Published findings
Full report
- agent-opt
- Trust report
- llm_agents
- Trust report
Shared compatibility
- Python · agent-opt: Python runtime · llm_agents: Python runtime
Choose agent-opt if…
- License: agent-opt is Apache-2.0, llm_agents is MIT.
- Tags unique to agent-opt: agent, ai-agents, aioptimization, automation.
- Also covers Evaluation & Observability.
- - When your project needs seamless CI/CD integration alongside automated optimization
When NOT to use agent-opt
- - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10
- - In scenarios where CI/CD integration is not a priority for your AI workflow optimization
Choose llm_agents if…
- License: llm_agents is MIT, agent-opt is Apache-2.0.
- Requirements: Min 1 GB RAM; Requires the installation of requirements specified by running `pip install -r requirements.txt` followed by `pip install -e .`.; Dependencies include setting up environment variables for `OPENAI_API_KEY` to use OpenAI API and optionally `SERPAPI_API_KEY` if Google search tool is utilized..
- Tags unique to llm_agents: deep-learning, langchain, llms, machine-learning.
- Use llm_agents when you require a lightweight solution for building agents controlled by LLMs with specific tools such as Python REPL execution or Hacker News search.
When NOT to use llm_agents
- Avoid llm_agents if you need a more robust and feature-rich product for complex tasks that require extensive integration capabilities beyond Python REPL, Google search, and Hacker News.
- Do not choose it when you are looking for advanced abstraction layers like those found in LangChain, as llm_agents aims to remain simple with fewer files and a straightforward core.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (future-agi/agent-opt) · observed Oct 3, 2026
- GitHub forks (future-agi/agent-opt) · observed Oct 3, 2026
- Last push (future-agi/agent-opt) · observed Jun 30, 2026
- License file (Apache-2.0) · observed Oct 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mpaepper/llm_agents) · observed Sep 20, 2026
- GitHub forks (mpaepper/llm_agents) · observed Sep 20, 2026
- Last push (mpaepper/llm_agents) · observed Jun 23, 2025
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-opt 75 · llm_agents 1.1k (synced Oct 3, 2026).
Common questions
- What is the difference between agent-opt and llm_agents?
- agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. llm_agents: Library to build agents controlled by LLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-opt over llm_agents?
- Choose agent-opt over llm_agents when License: agent-opt is Apache-2.0, llm_agents is MIT; Tags unique to agent-opt: agent, ai-agents, aioptimization, automation; Also covers Evaluation & Observability; - When your project needs seamless CI/CD integration alongside automated optimization.
- When should I choose llm_agents over agent-opt?
- Choose llm_agents over agent-opt when License: llm_agents is MIT, agent-opt is Apache-2.0; Requirements: Min 1 GB RAM; Requires the installation of requirements specified by running
pip install -r requirements.txtfollowed bypip install -e ..; Dependencies include setting up environment variables forOPENAI_API_KEYto use OpenAI API and optionallySERPAPI_API_KEYif Google search tool is utilized.; Tags unique to llm_agents: deep-learning, langchain, llms, machine-learning; Use llm_agents when you require a lightweight solution for building agents controlled by LLMs with specific tools such as Python REPL execution or Hacker News search. - When should I avoid agent-opt?
- - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - In scenarios where CI/CD integration is not a priority for your AI workflow optimization
- When should I avoid llm_agents?
- Avoid llm_agents if you need a more robust and feature-rich product for complex tasks that require extensive integration capabilities beyond Python REPL, Google search, and Hacker News. Do not choose it when you are looking for advanced abstraction layers like those found in LangChain, as llm_agents aims to remain simple with fewer files and a straightforward core.
- Is agent-opt or llm_agents more popular on GitHub?
- llm_agents has more GitHub stars (1,054 vs 75). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-opt and llm_agents open source?
- Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, llm_agents: MIT).
- Where can I find alternatives to agent-opt or llm_agents?
- GraphCanon lists graph-backed alternatives at agent-opt alternatives and llm_agents alternatives (agent-opt markdown twin, llm_agents markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agent-opt or llm_agents?
- agent-opt: Archived. llm_agents: 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 agent-opt and llm_agents?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-opt trust report; llm_agents trust report.