{"domain":"alloevil.github.io","status":"valid","tier":"listed","authority":45,"verified":false,"title":"agent-harness-evals","summary":"agent-harness-evals is a reconciliation layer over public AI evaluation leaderboards that exposes the model x agent-harness matrix model-only leaderboards hide: which harness gets the most out of each model, and how much the harness alone moves the score.","country":"US","country_source":"ip","publisher_country":null,"publisher_country_source":null,"hosting_country":"US","llms_txt":"https://alloevil.github.io/agent-harness-evals/llms.txt","llms_full_txt":"https://alloevil.github.io/agent-harness-evals/llms-full.txt","last_checked":"2026-10-24T10:01:34.000Z","agent_terms":null,"categories":["ai-ml"],"capabilities":[],"inferred_tags":["ai agent evaluation","agent harness","llm leaderboards","terminal-bench","benchmark matrix"],"audience":"developers","agent_uses":["read_docs","download_data","search_content"],"language":"en","platform_generated":false,"agent_summary":"agent-harness-evals: reconciles public AI evaluation leaderboards into a model x agent-harness matrix showing how much the harness moves benchmark scores.","llms_txt_cached":"https://agentwebmap.com/v1/domain/alloevil.github.io/llms.txt","agentic":"documentation","section_keys":["benchmarks","data","docs","evidence","source"],"section_partial":false,"section_indexed_at":"2026-10-24T10:01:40.815Z"}