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Agent DossierDifySafety 82/100

Xpersona Agent

个性化记忆助手

一个真正了解你的AI助手。该模板使用记忆逻辑,在实时对话中提取并存储关于你的事实、偏好和细节信息。 1. 从插件市场安装 OpenAI 插件。 2. 在 Dify 中授权 OpenAI:前往 工具 → OpenAI → 授权,并输入您的 API 密钥。 3. 在 **判断是否存储为记忆** LLM 节点中选择一个模型,用于判断用户消息中是否包含值得保存的事实、偏好或记忆(输出"Yes"或"No")。 4. 在 **提取记忆** LLM 节点中选择一个模型,将用户输入结构化为包含事实、偏好和记忆的 JSON 对象。 5. 在 **respond (1)** LLM 节点中选择一个模型,当无需存储新记忆时,使用现有记忆作为上下文回答用户。 6. 在 **respond (2)** LLM 节点中选择一个模型,在提取并追加新记忆后,基于最新记忆回答用户。

Trust evidence available

Overall rank

#86

Adoption

No public adoption signal

Trust

Unknown

Freshness

Oct 9, 2026

Freshness

Last checked Oct 9, 2026

Best For

个性化记忆助手 is best for workflow, support, openai workflows where documented compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, Dify, runtime-metrics, public facts pack

Overview

Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.

Verifiededitorial-content

Overview

Executive Summary

一个真正了解你的AI助手。该模板使用记忆逻辑,在实时对话中提取并存储关于你的事实、偏好和细节信息。 1. 从插件市场安装 OpenAI 插件。 2. 在 Dify 中授权 OpenAI:前往 工具 → OpenAI → 授权,并输入您的 API 密钥。 3. 在 **判断是否存储为记忆** LLM 节点中选择一个模型,用于判断用户消息中是否包含值得保存的事实、偏好或记忆(输出"Yes"或"No")。 4. 在 **提取记忆** LLM 节点中选择一个模型,将用户输入结构化为包含事实、偏好和记忆的 JSON 对象。 5. 在 **respond (1)** LLM 节点中选择一个模型,当无需存储新记忆时,使用现有记忆作为上下文回答用户。 6. 在 **respond (2)** LLM 节点中选择一个模型,在提取并追加新记忆后,基于最新记忆回答用户。 Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

No verified compatibility signals

Trust score

Unknown

Compatibility

Profile only

Freshness

Oct 9, 2026

Vendor

Dify

Artifacts

0

Benchmarks

0

Last release

Unpublished

Install & run

Setup Snapshot

  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence & Timeline

Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.

Verifiededitorial-content

Public facts

Evidence Ledger

Vendor (1)

Vendor

Dify

profilemedium
Observed Oct 9, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance

Events

Release & Crawl Timeline

Artifacts & Docs

Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.

Self-declaredDify

Captured outputs

Artifacts Archive

Extracted files

0

Examples

0

Snippets

0

Languages

zh-Hans

Editorial read

Docs & README

Docs source

Dify

Editorial quality

ready

一个真正了解你的AI助手。该模板使用记忆逻辑,在实时对话中提取并存储关于你的事实、偏好和细节信息。 1. 从插件市场安装 OpenAI 插件。 2. 在 Dify 中授权 OpenAI:前往 工具 → OpenAI → 授权,并输入您的 API 密钥。 3. 在 **判断是否存储为记忆** LLM 节点中选择一个模型,用于判断用户消息中是否包含值得保存的事实、偏好或记忆(输出"Yes"或"No")。 4. 在 **提取记忆** LLM 节点中选择一个模型,将用户输入结构化为包含事实、偏好和记忆的 JSON 对象。 5. 在 **respond (1)** LLM 节点中选择一个模型,当无需存储新记忆时,使用现有记忆作为上下文回答用户。 6. 在 **respond (2)** LLM 节点中选择一个模型,在提取并追加新记忆后,基于最新记忆回答用户。

Full README
  1. 从插件市场安装 OpenAI 插件。
  2. 在 Dify 中授权 OpenAI:前往 工具 → OpenAI → 授权,并输入您的 API 密钥。
  3. 在 判断是否存储为记忆 LLM 节点中选择一个模型,用于判断用户消息中是否包含值得保存的事实、偏好或记忆(输出"Yes"或"No")。
  4. 在 提取记忆 LLM 节点中选择一个模型,将用户输入结构化为包含事实、偏好和记忆的 JSON 对象。
  5. 在 respond (1) LLM 节点中选择一个模型,当无需存储新记忆时,使用现有记忆作为上下文回答用户。
  6. 在 respond (2) LLM 节点中选择一个模型,在提取并追加新记忆后,基于最新记忆回答用户。

API & Reliability

Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.

MissingDify

Machine interfaces

Contract & API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

No protocol metadata captured.

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/contract"
curl -s "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/trust"

Operational fit

Reliability & Benchmarks

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Machine Appendix

Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.

MissingDify

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": []
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "DIFY_MARKETPLACE",
      "generatedAt": "2026-10-09T03:19:03.545Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "workflow",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "support",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "openai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "capability:workflow|supported|profile capability:support|supported|profile capability:openai|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Dify",
    "href": "https://affiliate.dify.ai/06p00xtpqqwy-e8lw08?tid=3b916ed7-cb46-485a-b81f-10d2bddfd022",
    "sourceUrl": "https://affiliate.dify.ai/06p00xtpqqwy-e8lw08?tid=3b916ed7-cb46-485a-b81f-10d2bddfd022",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T01:20:55.813Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/dify-langgenius-bddfd-2/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[]

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