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SkillsBench founder shares the project's rapid growth from zero to 1600+ Discord members, 2 papers, and 150+ citations in under six months, along with extensive documentation.
SkillsBench 1.1 is released as the first audited, error-free benchmark for AI agent skills, showing rapid capability improvement from ~36% to 67% resolution rate and demonstrating that skills can substitute for model scale.
Introduces SkillDAG, a self-evolving typed directed graph for LLM skill selection at scale that models inter-skill relationships and allows agents to query and evolve the graph during execution, outperforming baselines on ALFWorld and SkillsBench.