customer-onboarding-call
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
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。
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
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
有潜力有用的候选项,但采用前应与替代方案比较。
信任
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。
审计
需审查对安装准备度、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。
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。
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
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
- 是
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
替代 Skill
amazon-listing-image-generation-editing
2 Stars
npx skills add wubin1836/ai-hive-agent-skills --skill amazon-listing-image-generation-editing
替代 Skill
gpt-image-2-product-image
2 Stars
npx skills add wubin1836/ai-hive-agent-skills --skill gpt-image-2-product-image
替代 Skill
ecommerce-video
2 Stars
npx skills add wubin1836/ai-hive-agent-skills --skill ecommerce-video
替代 Skill
ecommerce-main-image
2 Stars
npx skills add wubin1836/ai-hive-agent-skills --skill ecommerce-main-image
Agent 安全 v2
47/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
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。
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
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。
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-callAgent 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 JSON
/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/calle-ai-customer-onboarding-call/install
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。
安装交接
/api/skills/calle-ai-customer-onboarding-call/install
LLM 文本格式
/api/skills/calle-ai-customer-onboarding-call/install?format=text
寻找替代方案
/api/skills/search?q=customer-onboarding-call&limit=3
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-callRegistry 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。
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。
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在沙盒 Agent 中安装它,并端到端完成一次Customer support任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 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。
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。
工作流匹配
在这些场景使用此 Skill
Answer users
Customer support
I need my agent to triage support requests and draft useful replies from product knowledge.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Review risk
Legal and compliance
I need my agent to review contracts, privacy policies, or compliance documents and summarize risks.
工作流匹配
加入完整工作流
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Scrape, clean, and reuse web data
Web data pipeline
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
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gpt-image-2-product-image
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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
仓库近期活跃
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。
- 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。
增长闭环
分享工具包
为 customer-onboarding-call 准备的场景化草稿,可手动发布到 X。
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
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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Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- CALLE-AI
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
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这条 Registry 收录 列表归属于 CALLE-AI,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
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将证据徽章加入你的 README
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[](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call)
[](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call)
[](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call/audit)
[](https://www.openagentskill.com/skills/calle-ai-customer-onboarding-call)作者
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
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
仅限沙盒
- 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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