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
供給アセットの概要
マーケティングとグロース自動化
SEO、コンテンツ運用、リード獲得、CRM、メール自動化、分析、グロースのワークフローです。
シナリオ
Sales and CRM
I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.
Agent 適合
Claude Code + CLI + Codex
Codex、Claude Code、Cursor、CLI、またはカスタム Agent に対応します。
インストール
準備完了
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
メンテナンス
新しい
最終プッシュから 2 日
リスク
要レビュー
Permission surface may require sandboxing
GitHub 品質
63
65/100 品質 · 68/100 信頼
対象タグ
レビュー注記
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
Agent 導入スコアカード
信頼、監査、インストール準備状況を一目で確認
公開リポジトリのメタデータ、OpenAgentSkill のレビューシグナル、保守の鮮度、インストール準備状況を組み合わせたスコアです。候補選定の目安であり、人によるレビューの代替ではありません。
品質
有望有用な候補ですが、採用前に代替と比較してください。
信頼
サンドボックス限定信頼シグナルが不足または混在する有用な候補です。結果ループがタスク適合を示すまで、隔離されたワークスペースで使用してください。
監査
要レビューインストール準備、安全メタデータ、保守、採用リスクの機械可読なレビュー。
OpenAgentSkill Trust Score v5
インストール前に人のレビュー
実作業で使う前に、サンドボックスでのみ実行し、近い代替と比較してください。
スター
GitHub スター 63
リポジトリ活動
スター 63、フォーク 127
メンテナンス
最終プッシュから 2 日
ライセンス
MIT
インストール
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
インストール安全性
標準パッケージまたはランタイムのインストールパス
権限範囲
shell or command execution, network or browser access
Agent の成果
Agent の成果データはまだありません
ドキュメント
README/SKILL.md の文脈が十分です
リスク概要
本番前にレビュー
- 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
インストール準備状況
インストールパスを利用可能
- インストールパスを利用できます
- リポジトリの根拠を利用できます
- ライセンスが明示されています
- Agent-Proven の成果エビデンスはまだありません
Agent 可読メタデータ
このスキルの機械可読な判断データ。
このブロックまたは埋め込み JSON を使い、Agent がこのスキルをインストールすべきか、代替を選ぶべきか、先に人のレビューを求めるべきかを判断できます。
適したタスク
- Customer support ワークフロー
- Claude Code チーム
- builders willing to evaluate younger projects
- Read user messages
適した Agent
インストール判断
- コマンド
- npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
- ポリシー
- レビュー
- 人によるレビュー
- はい
信頼とリスク
- 信頼
- 60/100
- 監査
- 75/100
- リスクレベル
- 要レビュー
成果ループ
- エンドポイント
- /api/agent/outcome
- イベント ID
- resolve
- 成果
- 5
インストールコマンド
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call使わない場合
- ベンダー提供の SLA が必要なチーム
- 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.
- 高リスク権限のヒント: Shell またはコマンド実行
- Permission surface may require sandboxing
代替スキル
event-sales-script
128 スター
npx skills add bam-bam-2/solo-skills --skill event-sales-script
代替スキル
amazon-listing-image-generation-editing
2 スター
npx skills add wubin1836/ai-hive-agent-skills --skill amazon-listing-image-generation-editing
代替スキル
gpt-image-2-product-image
2 スター
npx skills add wubin1836/ai-hive-agent-skills --skill gpt-image-2-product-image
代替スキル
ecommerce-video
2 スター
npx skills add wubin1836/ai-hive-agent-skills --skill ecommerce-video
Agent セーフティ v2
47/100 · 自動インストールを避ける
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 またはコマンド実行
Skill メタデータに端末、CLI、Shell、サブプロセス、またはコマンド実行のワークフローが含まれます。
中
ネットワークアクセス
Skill はリモートページ、API、リポジトリ、外部サービスにアクセスする可能性があります。
中
データベースアクセス
Skill はスキーマを確認し、データベースを照会し、永続ストアを扱う可能性があります。
- 高リスク権限のヒント: Shell またはコマンド実行
- Permission surface may require sandboxing
インストール先
Agent ワークフローにこのスキルをインストール
公開インストールエンドポイントからコマンド、安全チェックリスト、対象プロンプト、正規リンクを取得します。
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 解決プラン
インストール前に Agent に適合性を検証させます。
Resolve API は第一候補、代替、安全ポリシー、監査メモ、インストール先、Agent がそのまま使えるプロンプトを返します。
JSON を開く
/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve テキスト
/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
インストール引き継ぎ
/api/skills/calle-ai-customer-onboarding-call/install
Agent が確認すべきこと
- Resolve API でタスク適合と代替を確認。
- 監査・信頼スコアと安全ポリシーの警告を確認。
- Codex、Claude Code、Cursor、CLI のインストール先互換性を確認。
プロンプトをコピー
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 引き継ぎ
別のディレクトリではなく、インストール経路を Agent に渡します。
公開インストールエンドポイントからコマンド、安全チェックリスト、対象プロンプト、正規リンクを取得します。
インストール引き継ぎ
/api/skills/calle-ai-customer-onboarding-call/install
LLM テキスト形式
/api/skills/calle-ai-customer-onboarding-call/install?format=text
代替を探す
/api/skills/search?q=customer-onboarding-call&limit=3
Agent プロンプト
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 メタデータ
自動スキル選択用の Agent 可読プロファイル。
Registry API 経由で判断、信頼、監査、ユースケース、インストールのシグナルを提供し、UI をスクレイピングせずに Agent が順位付けできます。
Manifest
/api/registry/manifest/calle-ai-customer-onboarding-call
LLM テキスト
/api/registry/manifest/calle-ai-customer-onboarding-call?format=text
インストール別名
/api/registry/install/calle-ai-customer-onboarding-call
推奨
/api/registry/recommend?task=Use%20customer-onboarding-call%20in%20an%20agent%20workflow&limit=3
Agent 適合
Customer support
プラットフォーム
Claude Code
Agent 判断パネル
Fallback candidate for Customer support
まずこのスキルでプロトタイプを作り、代替候補を用意してください。
スタック内の役割
代替候補
主な適合
Customer support
信頼ラベル
まずプロトタイプ
インストールパス
コマンド準備済み
使う場面
- Customer support ワークフロー
- Claude Code チーム
- builders willing to evaluate younger projects
根拠
- 最近のリポジトリ活動
- インストールコマンドまたは GitHub リポジトリが利用可能
- 品質プロファイル 65/100
- OpenAgentSkill エンゲージメント 5 件
先にレビュー
- 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.
実装パス
- 1サンドボックスの Agent にインストールし、Customer support タスクを一度最初から最後まで実行します。
- 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.
信頼プロファイル
サンドボックス限定
信頼シグナルが不足または混在する有用な候補です。結果ループがタスク適合を示すまで、隔離されたワークスペースで使用してください。
GitHub 採用度
確認GitHub スター 63
スター/フォーク活動
確認スター 63、フォーク 127; 現在のメタデータでは Issue 活動を利用できません
最近のメンテナンス
合格最終プッシュから 2 日
ライセンスの明確さ
合格MIT
良いシグナル
- AI レビュー承認済み
- インストールパスを利用できます
- リポジトリの根拠を利用できます
- 最近保守されたリポジトリ
- インストールコマンドに明確な高リスクパターンはありません
- 成果ループは準備済みですが、最初の実行が必要です
インストール前にレビュー
- 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
- 実際の Agent 成果レポートはまだありません
- 無人インストールの前に人によるレビューが必要です
推奨アクション
実作業で使う前に、サンドボックスでのみ実行し、近い代替と比較してください。
品質プロファイル
有望 Agent ワークフロー向けの候補
有用な候補ですが、採用前に代替と比較してください。
ワークフロー適合
このスキルを使うシナリオ
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.
ワークフロー適合
完全なワークフローに追加
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.
代替候補
インストール前に比較
このタスクに適する可能性のある類似スキル。
event-sales-script
커뮤니티 오프라인 행사를 카카오톡 단톡방과 스레드에서 판매하기 위한 세일즈 멘트 세트를 자동 생성하는 스킬. 행사 정보를 입력받아 선공개 공지, 개별 DM, 리스트 업데이트, 카운트다운, 중간 업데이트, 설문, 완판 공지 7단계 멘트를 채널별로 즉시 출력한다. 트리거: 행사 판매 멘트 만들어줘, 단톡 세일즈 문구, 티켓 판매 공지 써줘, 행사 홍보 문자, /event-sales-script
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。
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.
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.
概要
--- 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
技術詳細
- バージョン
- 1.0.0
- ライセンス
- MIT
- 最終更新
- 2026年8月21日
- 公開日
- 2026年8月21日
判断の要約
代替候補
最近のリポジトリ活動
Agent 実証エビデンス
Agent 実証エビデンス
Resolve、レビュー、インストール、限定実行後の成果レポート。
- 成功率
- —
- 直近の失敗
- —
- 成果
- 0
- 出力品質
- —
- 失敗
- 0
- 非該当
- 0
- インストール数
- 0
- リスクによりブロック
- 0
- 設定が必要
- 0
- 本番
- 0
Agent の実行結果はまだありません。最初の実行では /api/agent/outcome を通じて成功、設定要件、リスクによるブロック、失敗、非該当を報告できます。
成長ループ
共有キット
customer-onboarding-call 用のシナリオベース草案です。X へ手動投稿できます。
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
任意:インストールコマンド付きの返信
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
掲載元
Registry により登録
この掲載は公開ソースから登録されており、メンテナー申請が承認されるまで公式として表示されません。
- 作成者
- CALLE-AI
- インデックス作成者
- OpenAgentSkill コミュニティインデックス
帰属は公開リポジトリまたは作成者プロフィールにリンクされています。作成者は掲載を申請して所有権シグナルを更新できます。
このスキルを申請所有者の申請
このスキル掲載を申請
この Registry により登録 掲載は CALLE-AI に帰属していますが、まだ公式として表示されていません。申請すると、確認済み所有者シグナルが追加され、今後の公開、インストール、監査更新の信頼性が高まります。
クリエイター被リンクキット
README にエビデンスバッジを追加
開発者がリポジトリを評価する場所で、正規掲載、現在の信頼・監査シグナル、実際の Agent-Proven エビデンスを表示します。
[](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
プラットフォーム適合
健全性シグナル
- GitHub スター
- 63
- 品質スコア
- 36/100
- 最終 GitHub プッシュ
- 2026年8月21日
- フレームワークのヒント
- 不明
- OpenAgentSkill 閲覧数
- 5
- インストールコピー数
- 0
- 外部クリック
- 0
コミュニティシグナル
このスキルが Agent ワークフローに役立つかを共有してください。集約されたフィードバックがランキングを改善します。
信頼と安全性
サンドボックス限定
- GitHub 採用度GitHub スター 63確認
- スター/フォーク活動スター 63、フォーク 127; 現在のメタデータでは Issue 活動を利用できません確認
- 最近のメンテナンス最終プッシュから 2 日合格
- ライセンスの明確さMIT合格
- README/SKILL.md の完全性メタデータには十分な利用・ワークフロー文脈があります合格
- 依存関係/ランタイムのリスクcommand execution surface, network or browser surface情報
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