{
  "schemaVersion": "1.0",
  "item": {
    "slug": "agent-doppelganger",
    "name": "Agent Doppelgänger",
    "source": "tencent",
    "type": "skill",
    "category": "通讯协作",
    "sourceUrl": "https://clawhub.ai/sieershafilone/agent-doppelganger",
    "canonicalUrl": "https://clawhub.ai/sieershafilone/agent-doppelganger",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/agent-doppelganger",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=agent-doppelganger",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "manifest.yaml",
      "SKILL.md",
      "scripts/adg.py",
      "scripts/reanchor_style.py",
      "scripts/test_adg.py",
      "references/specification.md"
    ],
    "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."
        }
      ]
    },
    "sourceHealth": {
      "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/agent-doppelganger"
    },
    "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/agent-doppelganger",
    "agentPageUrl": "https://openagent3.xyz/skills/agent-doppelganger/agent",
    "manifestUrl": "https://openagent3.xyz/skills/agent-doppelganger/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/agent-doppelganger/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": "Agent Doppelgänger (ADG)",
        "body": "ADG is a policy-bounded identity proxy for real-world communication. It acts as a constrained autonomous delegate that communicates on your behalf within formally provable limits."
      },
      {
        "title": "Core Workflow",
        "body": "Adapter: Normalize incoming messages from various channels.\nIntent Analysis: Classify the intent along Domain, Stakes, Authority, and Ambiguity.\nPolicy Gate: Evaluate declarative policies (DSL) to determine if the agent is allowed to handle the request.\nConfidence Engine: Measure confidence in both intent analysis and proposed handling.\nResponse Generation: Synthesize a response using your Style, Heuristics, and Preferences.\nVerifier: Audit the response against hard constraints before sending or drafting."
      },
      {
        "title": "1. Identity Modeling",
        "body": "Identity is modeled as a composition of four layers:\n\nStyle: Surface form characteristics (length, directness, vocabulary).\nHeuristics: Core decision logic (e.g., \"avoid meetings without agenda\").\nPreferences: Soft weights (e.g., Work > Social).\nConstraints: Hard, user-defined rules."
      },
      {
        "title": "2. Authority & Policy",
        "body": "Policies are declarative and evaluated before any generation occurs. This ensures safety and prevents prompt injection from bypassing limits."
      },
      {
        "title": "3. Escalation",
        "body": "ADG automatically escalates to you (Draft or Block) if:\n\nPolicy is violated.\nConfidence falls below the defined threshold.\nThe request involves forbidden domains (Finance, Legal, Medical, etc.)."
      },
      {
        "title": "References",
        "body": "See specification.md for the full architectural blueprint.\nSee policy-dsl.md (To Be Created) for the formal policy language definition."
      },
      {
        "title": "Forbidden Modeling",
        "body": "ADG is strictly forbidden from modeling or handling:\n\nSecrets\nFinancial authority\nLegal intent\nPolitical opinions\nEmotional vulnerability/trauma"
      }
    ],
    "body": "Agent Doppelgänger (ADG)\n\nADG is a policy-bounded identity proxy for real-world communication. It acts as a constrained autonomous delegate that communicates on your behalf within formally provable limits.\n\nCore Workflow\nAdapter: Normalize incoming messages from various channels.\nIntent Analysis: Classify the intent along Domain, Stakes, Authority, and Ambiguity.\nPolicy Gate: Evaluate declarative policies (DSL) to determine if the agent is allowed to handle the request.\nConfidence Engine: Measure confidence in both intent analysis and proposed handling.\nResponse Generation: Synthesize a response using your Style, Heuristics, and Preferences.\nVerifier: Audit the response against hard constraints before sending or drafting.\nImplementation Details\n1. Identity Modeling\n\nIdentity is modeled as a composition of four layers:\n\nStyle: Surface form characteristics (length, directness, vocabulary).\nHeuristics: Core decision logic (e.g., \"avoid meetings without agenda\").\nPreferences: Soft weights (e.g., Work > Social).\nConstraints: Hard, user-defined rules.\n2. Authority & Policy\n\nPolicies are declarative and evaluated before any generation occurs. This ensures safety and prevents prompt injection from bypassing limits.\n\n3. Escalation\n\nADG automatically escalates to you (Draft or Block) if:\n\nPolicy is violated.\nConfidence falls below the defined threshold.\nThe request involves forbidden domains (Finance, Legal, Medical, etc.).\nReferences\nSee specification.md for the full architectural blueprint.\nSee policy-dsl.md (To Be Created) for the formal policy language definition.\nForbidden Modeling\n\nADG is strictly forbidden from modeling or handling:\n\nSecrets\nFinancial authority\nLegal intent\nPolitical opinions\nEmotional vulnerability/trauma"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/sieershafilone/agent-doppelganger",
    "publisherUrl": "https://clawhub.ai/sieershafilone/agent-doppelganger",
    "owner": "sieershafilone",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/agent-doppelganger",
    "downloadUrl": "https://openagent3.xyz/downloads/agent-doppelganger",
    "agentUrl": "https://openagent3.xyz/skills/agent-doppelganger/agent",
    "manifestUrl": "https://openagent3.xyz/skills/agent-doppelganger/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/agent-doppelganger/agent.md"
  }
}