{"id":"ccb8cf9c-594e-45b5-a6cd-3b6db7d2a6d9","slug":"clawhub-zning1994-brainharness-autoresearch","name":"BrainHarness Autoresearch","description":"Use when user wants to optimize, improve, benchmark, or evaluate a skill's prompt. Triggers on \"optimize skill\", \"improve skill prompt\", \"benchmark skill\", \"eval skill\", \"run autoresearch\", \"tune prompt\", \"prompt optimization\", \"skill evaluation\", \"A/B test prompt\", \"find best prompt\", \"auto-improve skill\". 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Triggers on \"optimize skill\", \"improve skill prompt\", \"benchmark skill\", \"eval skill\", \"run autoresearch\", \"tune prompt\", \"prompt optimization\", \"skill evaluation\", \"A/B test prompt\", \"find best prompt\", \"auto-improve skill\". Runs automated prompt experiments using the Karpathy autoresearch pattern.","source":"CLAWHUB","sourceId":"clawhub:s173qj6menrea848d3v13ma9qh83gb7k:brainharness-autoresearch","homepage":"https://clawhub.ai/zning1994/skills/brainharness-autoresearch","repository":"https://clawhub.ai/zning1994/brainharness-autoresearch","documentation":"https://www.xpersona.co/agent/clawhub-zning1994-brainharness-autoresearch","protocols":["OPENCLEW"],"examples":[{"kind":"example","language":"json","snippet":"{\n  \"test_inputs\": [\n    \"search for latest AI agent frameworks\",\n    \"find news about LLM inference optimization\",\n    \"搜一下 transformer 架构的最新进展\"\n  ],\n  \"evals\": [\n    {\n      \"name\": \"has_sources\",\n      \"type\": \"rule\",\n      \"rule\": \"regex\",\n      \"pattern\": \"(https?://|Source:|来源:)\"\n    },\n    {\n      \"name\": \"no_hallucinated_urls\",\n      \"type\": \"rule\",\n      \"rule\": \"banned_phrases\",\n      \"phrases\": [\"example.com\", \"placeholder.url\"]\n    },\n    {\n      \"name\": \"sufficient_detail\",\n      \"type\": \"rule\",\n      \"rule\": \"word_count\",\n      \"min\": 50,\n      \"max\": 500\n    },\n    {\n      \"name\": \"contains_summary\",\n      \"type\": \"rule\",\n      \"rule\": \"contains\",\n      \"values\": [\"summary\", \"key findings\", \"结论\"]\n    },\n    {\n      \"name\": \"no_apology_prefix\",\n      \"type\": \"rule\",\n      \"rule\": \"not_contains\",\n      \"values\": [\"I apologize\", \"I'm sorry, but\"]\n    },\n    {\n      \"name\": \"actionable_output\",\n      \"type\": \"llm\",\n      \"question\": \"Does the response provide actionable information the user can immediately use (links, specific facts, concrete next steps)?\",\n      \"pass_description\": \"The response contains specific actionable items like URLs, concrete facts, or clear next steps\",\n      \"fail_description\": \"The response is vague, generic, or lacks specific actionable information\"\n    }\n  ]\n}"},{"kind":"example","language":"bash","snippet":"python autoresearch.py \\\n  --target ../workspace/skills/brain-search/SKILL.md \\\n  --evals eval.json \\\n  --provider minimax \\\n  --runs 5 \\\n  --max-experiments 30 \\\n  --dashboard"}]}}