customer-onboarding-call

审查 · 60
已收录

Place a one-off welcome and onboarding call to a customer who just signed up, capture a structured result such as business type, goal, pain points, sentiment, and activation status, then write that result back to a CRM and queue a human follow-up task when the customer asks for o

Verified installs0
Stars63
版本1.0.0
质量65/100 · 有潜力
信任60/100 · 仅限沙盒
审计75/100 · 需审查

供给资产档案

营销与增长自动化

SEO、内容运营、线索获取、CRM、邮件自动化、分析与增长工作流。

浏览赛道

场景

Sales and CRM

I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.

适配 Agent

Claude Code + CLI + Codex

适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。

安装

就绪

npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call

维护状态

新鲜

距上次推送 1 天

风险

需审查

Permission surface may require sandboxing

GitHub 质量

63

65/100 质量 · 68/100 信任

覆盖标签

营销Sales and CRMbusinessagent-skill

审查说明

Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision

Agent 采用评分卡

一眼查看信任、审计与安装准备度

这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。

质量

有潜力
65

有用的候选项,但采用前应与替代方案比较。

信任

仅限沙盒
60

有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。

审计

需审查
75

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

OpenAgentSkill 信任评分 v5

安装前需人工审查

仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

63 个 GitHub Stars

仓库活跃度

63 个 Star,127 个 Fork

维护状态

距上次推送 1 天

许可证

MIT

安装

npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call

安装安全性

标准软件包或运行时安装路径

权限范围

shell or command execution, network or browser access

Agent 结果

暂未有 Agent 结果数据

文档

README/SKILL.md 上下文充分

风险摘要

生产前审查

  • The skill does not explicitly address how to handle failures when writing to the CRM or when the provider does not return structured results as expected.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: shell or command execution, network or browser access

安装准备度

安装路径可用

  • 安装路径可用
  • 仓库证据可用
  • 已声明许可证
  • 暂无 Agent 验证结果证据

Agent 可读元数据

这个 Skill 的机器可读决策数据。

使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。

打开 JSON

适用任务

  • Customer support 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects
  • Read user messages

适用 Agent

CodexClaude CodeCursorOpenAgentSkill CLICLI

安装决策

命令
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
策略
审查
人工审查

信任与风险

信任
60/100
审计
75/100
风险级别
需审查

结果闭环

端点
/api/agent/outcome
事件 ID
resolve
结果
5

安装命令

npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call

不适用场景

  • 需要厂商支持 SLA 的团队
  • production agents without a repository review
  • The skill does not explicitly address how to handle failures when writing to the CRM or when the provider does not return structured results as expected.
  • 高风险权限提示:Shell 或命令执行
  • Permission surface may require sandboxing

Agent 安全 v2

47/100 · 避免自动安装

实验性审查

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

通过 API 解析

Shell 或命令执行

Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。

网络访问

Skill 可能访问远程页面、API、仓库或外部服务。

数据库访问

Skill 可能检查 Schema、查询数据库或处理持久化存储。

  • 高风险权限提示:Shell 或命令执行
  • Permission surface may require sandboxing

安装目标

在你的 Agent 工作流中安装此 Skill

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install calle-ai-customer-onboarding-call

Agent 解析计划

让 Agent 在安装前验证匹配度。

Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。

打开文本计划

Agent 应检查

  • 从 Resolve API 检查任务匹配与替代方案。
  • 检查审计评分、信任评分和安全策略警告。
  • 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。

复制提示词

Task: Use customer-onboarding-call in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/calle-ai-customer-onboarding-call/install
Install command: npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent 交接

把安装路径交给 Agent,而不是再给一个目录页。

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

打开安装 API

Agent 提示词

Use customer-onboarding-call for this task. Review https://www.openagentskill.com/api/skills/calle-ai-customer-onboarding-call/install, then install with: npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call

Registry 元数据

用于自动选择 Skill 的 Agent 可读档案。

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。

打开 Manifest

适配 Agent

66/100

Customer support

平台

Claude Code

审计报告

需审查 · 75/100

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

查看审计报告查看评估报告

Agent 决策面板

Fallback candidate for Customer support

先用此 Skill 做原型验证,并保留备选方案。

66
就绪度
原型验证
阶段

栈中角色

备选候选

主要匹配

Customer support

信任标签

先做原型验证

安装路径

命令已就绪

适用场景

  • Customer support 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects

证据

  • 仓库近期活跃
  • 已提供安装命令或 GitHub 仓库
  • 65/100 质量档案
  • 5 个 OpenAgentSkill 交互事件

先审查

  • The skill does not explicitly address how to handle failures when writing to the CRM or when the provider does not return structured results as expected.

实施路径

  1. 1在沙盒 Agent 中安装它,并端到端完成一次Customer support任务。
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

信任档案

仅限沙盒

有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。

60
OpenAgentSkill 信任评分

GitHub 采用度

检查

63 个 GitHub Stars

Star/Fork 活跃度

检查

63 个 Star,127 个 Fork; 当前元数据中没有议题活跃度信息

近期维护

通过

距上次推送 1 天

许可证清晰度

通过

MIT

积极信号

  • AI 审查已通过
  • 安装路径可用
  • 仓库证据可用
  • 近期维护的仓库
  • 安装命令未发现明显高风险模式
  • 结果闭环已就绪,但需要首次真实 Agent 运行

安装前审查

  • The skill does not explicitly address how to handle failures when writing to the CRM or when the provider does not return structured results as expected.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: shell or command execution, network or browser access
  • GitHub adoption: 63 GitHub stars
  • Stars/forks activity: 63 stars, 127 forks; issue activity unavailable in current metadata
  • Permission surface: shell or command execution, network or browser access
  • 暂未有真实 Agent 结果报告
  • 无人值守安装前需要人工审查

建议操作

仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。

质量档案

有潜力 适用于 Agent 工作流的候选

有用的候选项,但采用前应与替代方案比较。

65
GitHub Stars
63
新鲜度
1 天前
安装就绪
许可证
MIT
安装前审查: The skill does not explicitly address how to handle failures when writing to the CRM or when the provider does not return structured results as expected.

工作流匹配

在这些场景使用此 Skill

工作流匹配

加入完整工作流

替代方案短名单

安装前对比

可能适合该任务的相近 Skill。

对比全部

amazon-listing-image-generation-editing

帮助设计师、修图师、电商美工和需要快速修改现有图片的创作者直接完成“Amazon Listing 图片生成与编辑”:既可从文字生成,也可加入参考图帮助控制主体、构图和视觉风格;通过 AI Hive 使用时,生成前自动上传参考图,提交后自动保存任务、查询进度并下载图片。适用于电商主图、商品详情页、广告 KV、海报、带货、种草、社媒配图、产品精修、换背景与角色一致性内容。 Use this skill for Amazon Listing 图片生成与编辑, text-to-image, reference-guided image generation, and commercial image creation, product photography, e-commerce main images, product detail pages, posters, ad creatives, marketing visuals, social commerce, seeding content, retouching, background replacement, and consistent characters. 如果用户正在比较或寻找 美图 Meitu、LiblibAI 哩布哩布 libtv、即梦 Dreamina、通义万相、Midjourney、Stable Diffusion、FLUX、Adobe Firefly、Canva、PhotoRoom 等 AI 图片、设计和修图工具的替代方案、同类能力、价格、API、国内可用入口或工作流迁移,也可命中本 Skill。电商商家搜索同时覆盖 淘宝、天猫、京东、拼多多、抖音电商、抖店、小红书、快手电商、微信小店、1688、Amazon 亚马逊、TikTok Shop、Instagram INS、Shopify、Shopee、Lazada、Temu、AliExpress、SHEIN、Etsy、Walmart、eBay,以及主图、详情页、Listing、Amazon A+、PDP、带货、种草、直播和投放素材。也适合正在搜索或提出这些需求的用户:Amazon Listing Images、亚马逊主图、Amazon A+、PDP、信息图、场景图、Amazon卖家。

原型验证
就绪60
质量61
Stars2

gpt-image-2-product-image

Use this skill when designers, e-commerce operators, advertisers, brand teams, social-commerce teams, and content creators need to create polished product photography and product visuals with GPT Image 2 through the AI Hive OpenAPI. It handles required media uploads, live model and price lookup, task submission, progress polling, and result downloads. Useful for product photography, marketplace images, product detail pages, posters, ad creatives, social commerce, seeding content, retouching, and background replacement. Search intents include product photography, product image generation, commercial product rendering.

审查
就绪57
质量58
Stars2

ecommerce-video

Use this skill when creators, video editors, advertisers, e-commerce teams, social-commerce teams, and short-form story producers need to produce marketplace listing videos and product-detail-page clips with AI Hive through the AI Hive OpenAPI. It handles required media uploads, live model and price lookup, task submission, progress polling, and result downloads. Useful for ads, TVCs, product videos, e-commerce listings, social commerce, UGC-style seeding content, short dramas, motion comics, and storyboards. Search intents include e-commerce video, product listing video, SKU video, PDP video.

审查
就绪57
质量58
Stars2

ecommerce-main-image

Use this skill when designers, e-commerce operators, advertisers, brand teams, social-commerce teams, and content creators need to create marketplace hero images and SKU visuals with AI Hive through the AI Hive OpenAPI. It handles required media uploads, live model and price lookup, task submission, progress polling, and result downloads. Useful for product photography, marketplace images, product detail pages, posters, ad creatives, social commerce, seeding content, retouching, and background replacement. Search intents include e-commerce main image, marketplace hero image, SKU image, product listing image.

审查
就绪57
质量58
Stars2

概览

--- name: customer-onboarding-call description: Place a one-off welcome and onboarding call to a customer who just signed up, capture a structured result such as business type, goal, pain points, sentiment, and activation status, then write that result back to a CRM and queue a human follow-up task when the customer asks for one. license: MIT ---

# Customer Onboarding Call

Use this skill when a new signup should receive a short welcome call and the business wants the conversation to end as structured data rather than as an unread recording.

`customer-onboarding-call` turns one signup event into at most one **conversation**, one structured result, and at most one follow-up task. Obtaining that conversation may take up to three attempts on an unreliable corridor, with only one attempt in flight at a time; see *Attempts, Retries, and Cancellation*. It does not create recurring schedules, call campaigns, or contact lists. Recurrence, if the business wants it, belongs to the host scheduler; see [`call-reminder`](../call-reminder/).

The workflow is deliberately narrow: welcome, consent, discovery, next-step offer, wrap-up. A call that tries to sell, negotiate, collect payment, or resolve a support ticket is out of scope.

## When To Use

Use this skill for:

- welcoming a customer who just signed up and confirming they can get started - collecting first-party onboarding context: business type, goal, prior tooling, blockers - detecting whether a customer wants a human to follow up - turning a spoken answer into a CRM field and an assigned task - measuring activation coverage when a team cannot call every signup manually

## When Not To Use

Do not use this skill to:

- call people who did not sign up or otherwise ask to be contacted - run sales, collections, renewal, or win-back calls - deliver medical, legal, financial, or emergency instructions - read pricing, delivery windows, contractual terms, or policy from memory - retry indefinitely after a customer declines or asks not to be called - re-call a customer who has already completed an onboarding call, unless the user explicitly asks

## Required Fields

For each call, require:

- `customerName` - `phoneNumber` in E.164 - `companyName` for the agent to introduce itself as - `companyDescription`, one sentence the agent may state as fact

Optional:

- `businessName` - `locale` and `region` hints for the conversation

Ask for any missing required field. Do not infer a phone number, country code, or region from a locale, an IP address, an email domain, or unrelated prior context.

## Core Workflow

1. Confirm the signup is real and recent, and that this customer has not already been called. 2. Build the call task from the required fields. Keep the script to roughly two minutes. 3. Attach a structured result schema so the provider returns fields, not just a transcript. See [`references/structured-result.md`](references/structured-result.md). 4. Persist an attempt record under a uniqueness constraint on `(signup_id, attempt_no)` **before** dialing, and derive the provider idempotency key from it. Refuse to start a new attempt while another is in flight for the same signup. 5. Place the call for that attempt. 6. Receive the terminal result on a webhook. Treat delivery as at-least-once and key ingestion on the provider event id. 7. Classify the outcome before writing anything: Stage A decides whether a human took part, and only then does Stage B read consent. See *Outcome Classification* below. 8. Write only what the outcome permits, then queue a follow-up task only when the outcome is `onboarded` and the customer asked for one. 9. Schedule or cancel a retry according to *Attempts, Retries, and Cancellation*.

Use this shape:

```text signup -> attempt record -> call task + result schema -> attempt -> terminal webhook -> classify -> permitted CRM write -> follow-up or retry or suppress ```

## Conversation Shape

Keep the call in this order. Allow interruption at any point.

1. **Greet and identify.** Name the customer, name the company, state that the call may be recorded if that is true in your jurisdiction. 2. **Ask consent.** Ask whether now is a good time for a short call. If the answer is no, offer to call back later and end. Do not continue discovery after a soft refusal. 3. **Discovery.** Ask what kind of business they run, why they signed up, what problem they want solved, and whether they have used something similar before. One question at a time. 4. **Offer the next step.** Invite the concrete first action, and offer a human if they prefer. 5. **Wrap up.** Summarize what will happen next, thank them, end.

The agent may answer only from `companyDescription` and any knowledge base you explicitly supply. For anything else — price, delivery time, policy, availability — it must say it will have a human follow up. Inventing these is the most common failure mode of onboarding-call agents.

## State Machine

The full contract in one view. Every arrow that ends in a call is guarded; every terminal state says what it permits.

```text signup | v [ allocate attempt no > cap? ]---- yes -->( manual handling ) | ^ no | v | [ attempt live (leased) ] | | | +-------------------+--------------------+ | | | | | terminal result lease expires create failed | | | | | | v | | | [ reconcile with provider ] | | | | | | | | | terminal still live unknown | | | | | | | | +<------------+ v | | | | ( ambiguous )-+-------+ | | | (late result re-enters) | v | | == STAGE A: was a human reached? == | reachability from CALL EVIDENCE, not from "is there a result" | | | +-- refusal evidence present? --> ( declined ) | | | no-human — CLOSED evidence set only: voicemail / carrier msg / ring-out / no-answer / silence / provider machine signal | +--> ( not-reached ) ------------------ retry allowed ---+ | | +--> ( failed ) provider positively says NO CALL PLACED --+ | +--> ( needs-review ) indeterminate: provider unreachable, | unknown attempt, expired lease, extractor-only NotReached, | billing charge with no obtainable outcome. NO RETRY. | human v == STAGE B: consent governs == | +--> ( declined ) terminal. suppress per scope. no follow-up, no retry, ever. +--> ( needs-review ) no result at all, unusable consent fields, or indeterminate | reachability. terminal until a human decides. NO auto retry. +--> ( partial ) write captured fields only. retry ONLY with callback consent | or human authorisation, and only under the cap. +--> ( onboarded ) write insight. follow-up only if requested. ```

Invariants the diagram encodes:

- **A redial requires positive no-human evidence from a closed set.** A missing result, an extractor-claimed `NotReached`, an unreachable provider, an expired lease, and a billing charge are all *unknown* — they route to `needs-review`, never to a retry. - **Releasing a stuck attempt and authorising a redial are separate decisions.** Unblocking the slot is bookkeeping; dialling again needs evidence. - **Refusal evidence dominates.** It routes to `declined` from anywhere, with or without a result. - **Only Stage B can suppress a number**, and only via `declined`. - **Only Stage A outcomes retry automatically.** Every Stage B redial needs consent or a human, and anything uncertain lands in `needs-review`, which never retries. - **No state is permanent-by-accident.** A live attempt is leased, and `ambiguous` is provisional — a late result re-enters classification from the top. - **The cap bounds every path**, including callback-consented redials.

## Outcome Classification

A call that reaches a terminal state has not necessarily reached a consenting human. Providers commonly return a completed call with an empty structured result when the agent talked to a carrier message, voicemail, or silence. A call can also produce a perfectly well-formed structured result while the customer was refusing to take part.

**The presence of a structured result is not evidence of consent.** Classification is therefore driven by an evidence-backed `disposition` field, not by whether a result exists. See [`references/structured-result.md`](references/structured-result.md).

Classify in **two stages, in this order**. Stage A decides whether a human took part at all. Only if one did does Stage B read consent.

The staging is the contract, not a presentation choice. Consent fields are meaningless when nobody answered — a voicemail grants no consent, so `consent_granted` is `false` there. Reading consent before establishing that a human was reached turns every no-answer into a refusal.

### Stage A — was a human reached?

**Reachability is decided on call evidence, never on whether a structured result exists.** A real conversation can return no result at all: extraction failed, the result failed validation, or the customer refused and rang off before the model emitted anything. Inferring "nobody answered" from a missing result would auto-retry those calls and redial a person who may have just refused.

#### The no-human evidence set

Exactly one thing authorises an automatic redial: **observed evidence from the call itself that no person took part.** This is a closed list.

| Counts as no-human evidence | | | --- | --- | | voicemail or answering-machine greeting | carrier or network announcement | | ring-out with no answer | the provider's own answered-by-machine / no-answer signal | | silence throughout after the agent spoke | |

**Nothing else qualifies.** In particular these are *not* no-human evidence, however tempting:

- a missing or empty structured result - the extractor's own `disposition: NotReached` — that is a model claim about the call, not an observation of it, and the same extractor mislabels refusals - a provider that is unreachable, times out, or has no record of the attempt - an expired lease - a billing charge or usage record — that shows a call *was placed*, which if anything makes a conversation more likely, not less

Every one of those means **we do not know**. Unknown is `needs-review`, never a retry. The asymmetry is deliberate: a needless manual check costs a minute, and a wrong redial reaches someone who may have already refused.

#### Establishing reachability

| Reachability | Evidence | | --- | --- | | `human` | the provider reports a human answered, **or** the transcript contains customer speech that is not carrier or IVR audio | | `no-human` | at least one item from the no-human evidence set above, and no contradicting customer speech | | `indeterminate` | anything else, including every "not evidence" item listed above |

#### Then

技术详情

版本
1.0.0
许可证
MIT
最近更新
2026年8月21日
发布时间
2026年8月21日

决策摘要

备选候选

66
就绪
原型验证
阶段

仓库近期活跃

审计

安装审查

安装与采用审查

75
需审查
安全性
75/100
维护状态
100/100
安装
92/100
打开完整审计查看评估报告

Agent 验证证据

Agent 验证证据

来自解析、审查、安装和一次小范围运行后的结果报告。

0
已验证
Needs first agent run自动安装: 先审查最近: 未知
成功率
近期失败
结果
0
输出质量
失败
0
不相关
0
安装次数
0
风险拦截
0
需要配置
0
生产环境
0

暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。

安装

加入 Agent 工作流

免费且开源. 在生产 Agent 中安装前请先审查报告。

增长闭环

分享工具包

X

为 customer-onboarding-call 准备的场景化草稿,可手动发布到 X。

策展说明
customer-onboarding-call: Place a one-off welcome and onboarding call to a customer who just signed up, capture a struc...

63 stars

https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call?ref=x
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可选:带安装命令的回复
Listing + install path for customer-onboarding-call:
https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call?ref=x

Install: npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
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CALLE-AI
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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/calle-ai-customer-onboarding-call?metric=listed&label=Listed)](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/calle-ai-customer-onboarding-call?metric=trust&label=Trust)](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/calle-ai-customer-onboarding-call?metric=audit&label=Audit)](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/calle-ai-customer-onboarding-call?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call)

作者

C

CALLE-AI

@calle-ai

平台适配

健康信号

GitHub Stars
63
质量评分
36/100
最近 GitHub 推送
2026年8月21日
框架提示
未知
OpenAgentSkill 浏览量
5
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0
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0

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信任与安全

仅限沙盒

60
  • GitHub 采用度63 个 GitHub Stars检查
  • Star/Fork 活跃度63 个 Star,127 个 Fork; 当前元数据中没有议题活跃度信息检查
  • 近期维护距上次推送 1 天通过
  • 许可证清晰度MIT通过
  • README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
  • 依赖与运行时风险command execution surface, network or browser surface信息

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