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
Supply asset profile
Marketing and growth automation
SEO, content operations, lead generation, CRM, email automation, analytics, and growth workflows.
Scenario
Sales and CRM
I need my agent to enrich leads, update CRM records, and prepare sales follow-ups.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
Maintenance
fresh
1d since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
63
65/100 Quality · 68/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
63 GitHub stars
Repo activity
63 stars, 127 forks
Maintenance
1d since push
License
MIT
Install
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
Install safety
standard package or runtime install path
Permission surface
shell or command execution, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- 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
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- Customer support workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Read user messages
Suited agents
Install decision
- Command
- npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-call
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 60/100
- Audit
- 75/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add CALLE-AI/awesome-phone-call-agents --skill customer-onboarding-callDo not use when
- teams that need a vendor-supported SLA
- 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.
- High-risk permission hints: Shell or command execution
- Permission surface may require sandboxing
Agent safety v2
47/100 · Avoid automatic install
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Shell or command execution
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Database access
Skill may inspect schemas, query databases, or work with persistent stores.
- High-risk permission hints: Shell or command execution
- Permission surface may require sandboxing
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
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 resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20customer-onboarding-call%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/calle-ai-customer-onboarding-call/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
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 handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/calle-ai-customer-onboarding-call/install
LLM text format
/api/skills/calle-ai-customer-onboarding-call/install?format=text
Find alternatives
/api/skills/search?q=customer-onboarding-call&limit=3
Agent prompt
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 metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/calle-ai-customer-onboarding-call
LLM text
/api/registry/manifest/calle-ai-customer-onboarding-call?format=text
Install alias
/api/registry/install/calle-ai-customer-onboarding-call
Recommend
/api/registry/recommend?task=Use%20customer-onboarding-call%20in%20an%20agent%20workflow&limit=3
Agent fit
Customer support
Platforms
Claude Code
Audit report
Needs review · 75/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for Customer support
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Customer support
Trust label
Prototype first
Install path
Command ready
Use when
- Customer support workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 65/100 quality profile
- 4 OpenAgentSkill engagement events
review first
- 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.
Implementation path
- 1Install it in a sandbox agent and run one Customer support task end to end.
- 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.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
CHECK63 GitHub stars
Stars/forks activity
CHECK63 stars, 127 forks; issue activity unavailable in current metadata
Recent maintenance
PASS1d since push
License clarity
PASSMIT
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- 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
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
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.
Workflow fit
Add it to a complete workflow
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.
Alternative shortlist
Compare before you install
Similar skills that may fit this task.
ew
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Overview
--- 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
Technical details
- Version
- 1.0.0
- License
- MIT
- Last updated
- Aug 21, 2026
- Published
- Aug 21, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 75/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for customer-onboarding-call, ready for a manual X post.
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
Optional reply with install command
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
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- CALLE-AI
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to CALLE-AI but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](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)Author
CALLE-AI
@calle-ai
Tags
Platform fit
Health signals
- GitHub stars
- 63
- Quality score
- 36/100
- Last GitHub push
- Aug 21, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 4
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption63 GitHub starsCHECK
- Stars/forks activity63 stars, 127 forks; issue activity unavailable in current metadataCHECK
- Recent maintenance1d since pushPASS
- License clarityMITPASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime riskcommand execution surface, network or browser surfaceINFO
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