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Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms.
Passed 21 of 21 test cases with the skill, and 5 of 21 without it.
and 25 more in the full report
17 fixed5 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
I want to benchmark software patch generation tasks using Claude Opus 4.6 with built-in verify-fix loop capabilities. What built-in seed agent name should I specify when initializing the evolver?
| Checked | Without skill | With skill |
|---|---|---|
| Names swe as the built-in seed agent string. | Missed | Passed |
The instructions your model reads when the skill loads.
A-Evolve is universal infrastructure for evolving any AI agent across any domain using any evolution algorithm with zero manual engineering. It represents all evolvable agent state as files (prompts, skills, memory, tools), runs iterative solve-observe-evolve cycles against benchmarks, and uses LLM-driven mutation to improve agent performance automatically.
Benchmark results (Claude Opus 4.6):
Use A-Evolve when:
Key differentiator: Other frameworks build agents; A-Evolve optimizes them. It sits on top of any agent framework and makes it better through automated evolution.
Do NOT use A-Evolve for:
pip install a-evolve # Core
pip install a-evolve[anthropic] # With Claude support
pip install a-evolve[all] # All providers
test cases passed, vs 5 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.