{
  "schemaVersion": "1.0",
  "item": {
    "slug": "curiosity-engine",
    "name": "Curiosity Engine",
    "source": "tencent",
    "type": "skill",
    "category": "效率提升",
    "sourceUrl": "https://clawhub.ai/luofulily1-cmyk/curiosity-engine",
    "canonicalUrl": "https://clawhub.ai/luofulily1-cmyk/curiosity-engine",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/curiosity-engine",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=curiosity-engine",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "SKILL.md",
      "references/examples.md",
      "references/theory.md",
      "scripts/curiosity_eval.py"
    ],
    "primaryDoc": "SKILL.md",
    "quickSetup": [
      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
    "agentAssist": {
      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
        "Extract it into a folder your agent can access.",
        "Paste one of the prompts below and point your agent at the extracted folder."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
        }
      ]
    },
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      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-23T16:43:11.935Z",
      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
        "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/curiosity-engine"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/curiosity-engine",
    "agentPageUrl": "https://openagent3.xyz/skills/curiosity-engine/agent",
    "manifestUrl": "https://openagent3.xyz/skills/curiosity-engine/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/curiosity-engine/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Curiosity Engine",
        "body": "Enhance agent reasoning with structured curiosity behaviors during inference.\nThis skill does not require training — it reshapes how you think at runtime."
      },
      {
        "title": "Core Loop: OODA-C (Observe → Orient → Doubt → Act → Curiose)",
        "body": "For every non-trivial question, run this loop before answering:"
      },
      {
        "title": "1. OBSERVE — What do I see?",
        "body": "State the facts from the user's input\nNote what tools/information are available"
      },
      {
        "title": "2. ORIENT — What do I think I know?",
        "body": "Form an initial hypothesis\nRate confidence: HIGH (8-10) / MEDIUM (5-7) / LOW (1-4)"
      },
      {
        "title": "3. DOUBT — Challenge yourself (the curiosity step)",
        "body": "Run the three doubt protocols:\n\nProtocol A: Self-Ask (from Self-Questioning)\n\nGenerate 3 questions this input raises that weren't explicitly asked\nPick the one with highest expected information gain\nAsk: \"If I knew the answer to this, would it change my response?\"\nIf YES → investigate before answering\n\nProtocol B: Devil's Advocate (from Assumption Challenging)\n\nList 2 assumptions your hypothesis depends on\nFor each: \"What if this assumption is wrong?\"\nIf an alternative explanation survives → flag it\n\nProtocol C: Gap Map (from Information Gap Detection)\n\nCategorize your knowledge:\n\n✅ KNOWN: Facts I can verify\n⚠️ ASSUMED: Things I believe but haven't checked\n❌ UNKNOWN: Missing info that matters\n\n\nFor each ❌ item: Can I fill this gap with available tools?"
      },
      {
        "title": "4. ACT — Explore with tools",
        "body": "For each actionable gap from step 3:\n\nUse web_search, web_fetch, read, exec as appropriate\nRecord what you found and whether it confirmed or changed your thinking\n\n\nPrioritize: highest information gain first, max 3 tool explorations per loop"
      },
      {
        "title": "5. CURIOSE — Reflect and branch",
        "body": "Did anything surprise you? If yes, note it explicitly\nHas your confidence rating changed? Update it\nNew questions emerged? Log them as \"open threads\"\nDecide: loop again (if confidence < 7) or respond"
      },
      {
        "title": "When to Activate",
        "body": "Always activate (full loop):\n\nOpen-ended research questions\nUser says \"dig deeper\", \"explore\", \"investigate\", \"be curious\"\nYou encounter a fact that contradicts your expectations\nConfidence on initial hypothesis < 5\n\nLight activation (Protocol C only):\n\nFactual questions with some uncertainty\nTasks where you have tools available but aren't sure you need them\n\nSkip (answer directly):\n\nSimple factual lookups (weather, time, definitions)\nUser explicitly wants a quick answer\nRoutine tasks (file operations, formatting)"
      },
      {
        "title": "Curiosity Behaviors (always-on)",
        "body": "Even outside the full loop, maintain these habits:"
      },
      {
        "title": "Surprise Detector",
        "body": "When you encounter information that is:\n\nCounter-intuitive\nContradicts common belief\nStatistically unusual\nConnects two seemingly unrelated domains\n\n→ Flag it with 🔍 and spend 1 extra step investigating"
      },
      {
        "title": "One More Step Rule",
        "body": "Before finalizing any research-type answer, ask:\n\n\"Is there one more thing I could check that would meaningfully improve this answer?\"\nIf yes and tools are available → do it."
      },
      {
        "title": "Open Thread Tracker",
        "body": "When curiosity leads to questions you can't answer right now:\n\nLog them at the end of your response under \"🧵 Open Threads\"\nThese become seeds for future exploration\nUser can say \"follow thread N\" to continue"
      },
      {
        "title": "Output Format",
        "body": "When the full loop runs, structure your response as:\n\n🔍 Curiosity Engine Active\n\n[Your actual response — thorough, informed by exploration]\n\n---\n📊 Confidence: X/10 (changed from Y/10 after exploration)\n🔍 Surprises: [anything unexpected you found]\n🧵 Open Threads:\n  1. [question for future exploration]\n  2. [question for future exploration]\n\nFor light activation, skip the header — just naturally incorporate the extra depth."
      },
      {
        "title": "Anti-Patterns (avoid these)",
        "body": "❌ Exploring when user needs a quick answer\n❌ More than 3 tool calls in a single curiosity loop (diminishing returns)\n❌ Reporting the loop mechanics — show the results, not the process\n❌ Fake curiosity — don't pretend surprise. If nothing surprises you, say so\n❌ Infinite loops — max 2 OODA-C iterations per response"
      },
      {
        "title": "Integration with OpenClaw",
        "body": "This skill works best when the agent has:\n\nweb_search / web_fetch — for filling knowledge gaps\nread / exec — for verifying assumptions against real data\nmemory files — for persisting open threads across sessions\n\nStore persistent open threads in memory/curiosity-threads.md if the user opts into memory."
      },
      {
        "title": "Tuning",
        "body": "Users can adjust curiosity level:\n\n/curious off — disable, answer directly\n/curious low — Protocol C only (gap detection)\n/curious high — full OODA-C loop on everything\n/curious auto — default, skill decides based on question type"
      },
      {
        "title": "Theory (for context, not for output)",
        "body": "This skill operationalizes:\n\nSchmidhuber's Compression Progress: pursue information that improves your model fastest\nFriston's Active Inference: act to reduce expected uncertainty\nBayesian Surprise: prioritize information that most changes your beliefs\nInformation Gap Theory (Loewenstein): curiosity = felt deprivation from knowing you don't know\n\nThe OODA-C loop translates these into executable inference-time behaviors without requiring access to model internals."
      }
    ],
    "body": "Curiosity Engine\n\nEnhance agent reasoning with structured curiosity behaviors during inference. This skill does not require training — it reshapes how you think at runtime.\n\nCore Loop: OODA-C (Observe → Orient → Doubt → Act → Curiose)\n\nFor every non-trivial question, run this loop before answering:\n\n1. OBSERVE — What do I see?\nState the facts from the user's input\nNote what tools/information are available\n2. ORIENT — What do I think I know?\nForm an initial hypothesis\nRate confidence: HIGH (8-10) / MEDIUM (5-7) / LOW (1-4)\n3. DOUBT — Challenge yourself (the curiosity step)\n\nRun the three doubt protocols:\n\nProtocol A: Self-Ask (from Self-Questioning)\n\nGenerate 3 questions this input raises that weren't explicitly asked\nPick the one with highest expected information gain\nAsk: \"If I knew the answer to this, would it change my response?\"\nIf YES → investigate before answering\n\nProtocol B: Devil's Advocate (from Assumption Challenging)\n\nList 2 assumptions your hypothesis depends on\nFor each: \"What if this assumption is wrong?\"\nIf an alternative explanation survives → flag it\n\nProtocol C: Gap Map (from Information Gap Detection)\n\nCategorize your knowledge:\n✅ KNOWN: Facts I can verify\n⚠️ ASSUMED: Things I believe but haven't checked\n❌ UNKNOWN: Missing info that matters\nFor each ❌ item: Can I fill this gap with available tools?\n4. ACT — Explore with tools\nFor each actionable gap from step 3:\nUse web_search, web_fetch, read, exec as appropriate\nRecord what you found and whether it confirmed or changed your thinking\nPrioritize: highest information gain first, max 3 tool explorations per loop\n5. CURIOSE — Reflect and branch\nDid anything surprise you? If yes, note it explicitly\nHas your confidence rating changed? Update it\nNew questions emerged? Log them as \"open threads\"\nDecide: loop again (if confidence < 7) or respond\nWhen to Activate\n\nAlways activate (full loop):\n\nOpen-ended research questions\nUser says \"dig deeper\", \"explore\", \"investigate\", \"be curious\"\nYou encounter a fact that contradicts your expectations\nConfidence on initial hypothesis < 5\n\nLight activation (Protocol C only):\n\nFactual questions with some uncertainty\nTasks where you have tools available but aren't sure you need them\n\nSkip (answer directly):\n\nSimple factual lookups (weather, time, definitions)\nUser explicitly wants a quick answer\nRoutine tasks (file operations, formatting)\nCuriosity Behaviors (always-on)\n\nEven outside the full loop, maintain these habits:\n\nSurprise Detector\n\nWhen you encounter information that is:\n\nCounter-intuitive\nContradicts common belief\nStatistically unusual\nConnects two seemingly unrelated domains\n\n→ Flag it with 🔍 and spend 1 extra step investigating\n\nOne More Step Rule\n\nBefore finalizing any research-type answer, ask:\n\n\"Is there one more thing I could check that would meaningfully improve this answer?\" If yes and tools are available → do it.\n\nOpen Thread Tracker\n\nWhen curiosity leads to questions you can't answer right now:\n\nLog them at the end of your response under \"🧵 Open Threads\"\nThese become seeds for future exploration\nUser can say \"follow thread N\" to continue\nOutput Format\n\nWhen the full loop runs, structure your response as:\n\n🔍 Curiosity Engine Active\n\n[Your actual response — thorough, informed by exploration]\n\n---\n📊 Confidence: X/10 (changed from Y/10 after exploration)\n🔍 Surprises: [anything unexpected you found]\n🧵 Open Threads:\n  1. [question for future exploration]\n  2. [question for future exploration]\n\n\nFor light activation, skip the header — just naturally incorporate the extra depth.\n\nAnti-Patterns (avoid these)\n❌ Exploring when user needs a quick answer\n❌ More than 3 tool calls in a single curiosity loop (diminishing returns)\n❌ Reporting the loop mechanics — show the results, not the process\n❌ Fake curiosity — don't pretend surprise. If nothing surprises you, say so\n❌ Infinite loops — max 2 OODA-C iterations per response\nIntegration with OpenClaw\n\nThis skill works best when the agent has:\n\nweb_search / web_fetch — for filling knowledge gaps\nread / exec — for verifying assumptions against real data\nmemory files — for persisting open threads across sessions\n\nStore persistent open threads in memory/curiosity-threads.md if the user opts into memory.\n\nTuning\n\nUsers can adjust curiosity level:\n\n/curious off — disable, answer directly\n/curious low — Protocol C only (gap detection)\n/curious high — full OODA-C loop on everything\n/curious auto — default, skill decides based on question type\nTheory (for context, not for output)\n\nThis skill operationalizes:\n\nSchmidhuber's Compression Progress: pursue information that improves your model fastest\nFriston's Active Inference: act to reduce expected uncertainty\nBayesian Surprise: prioritize information that most changes your beliefs\nInformation Gap Theory (Loewenstein): curiosity = felt deprivation from knowing you don't know\n\nThe OODA-C loop translates these into executable inference-time behaviors without requiring access to model internals."
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/luofulily1-cmyk/curiosity-engine",
    "publisherUrl": "https://clawhub.ai/luofulily1-cmyk/curiosity-engine",
    "owner": "luofulily1-cmyk",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/curiosity-engine",
    "downloadUrl": "https://openagent3.xyz/downloads/curiosity-engine",
    "agentUrl": "https://openagent3.xyz/skills/curiosity-engine/agent",
    "manifestUrl": "https://openagent3.xyz/skills/curiosity-engine/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/curiosity-engine/agent.md"
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}