Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add CALLE-AI/awesome-phone-call-agents --skill shop-voice-checkingit clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/shop-voice-checkin)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/shop-voice-checkin"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/shop-voice-checkin/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/shop-voice-checkin"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/shop-voice-checkin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.02253 |
| Opus 5.5 | $0.00018 | $0.00901 |
| Sonnet 5.5 | $0.00009 | $0.00451 |
| Haiku 4.5 | $0.00005 | $0.00225 |
Grade A, and why
shop-voice-checkin scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shop Voice Check-in
Use this skill when a shop owner has opted in to regular phone check-ins instead of entering data into an app. The agent calls, speaks in simple English, Pidgin-influenced English, or Hindi-English (Hinglish), asks about stock and sales, and returns structured JSON for a local shop ledger.
This skill is the voice layer of Voice Shop Manager — "your business manager, on the phone."
When to use
- Morning inventory check-in — approximate stock levels, low items, supplier mentions
- Evening sales recap — approximate daily revenue, top sellers, restock spend
- Voice-first workflows for informal retailers in Nigeria, West Africa, or similar markets (India via English/Hindi task variants)
Pair with the runnable app at apps/python/shop-voice-manager/ (relative to this submission repository root) to persist results in SQLite and generate weekly summaries.
Demo mode: Default hackathon path uses fixtures — no live call. See references/demo-mode.md.
When not to use
- Cold-calling retailers who did not consent
- Loan offers, credit scoring conversations, or regulated financial advice on the call
- Replacing a POS, accounting system, or tax filing workflow
- Batch supplier procurement calls without explicit authorization per recipient
- Recurring schedules without a separate scheduler wrapper — see
call-reminder
Required fields
For each call, require:
shop_id— stable identifier for the retailercall_type—inventory,sales,reorder_offer,vendor_order,order_status, oronboardingphone— E.164 number of the consenting shop owner (or, forvendor_order, the consenting vendor)region— CALL-E region code, e.g.NGorINlocale— CALL-E locale, e.g.enrecipient_consented— must betruefor live calls
Optional:
currency—NGN,INR, etc.language_style—pidgin-english,english, orhindi-englishproducts_to_ask— short list for morning check-instimezone— IANA name for scheduling context
What ships with it
19 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/example-request-inr.template.json 317 B
- assets/example-request.template.json 358 B
- assets/sample-shop-profile-inr.json 603 B
- assets/sample-shop-profile.json 610 B
- references/call-scripts-english.md 4.8 KB
- references/call-scripts-hindi-english.md 5.2 KB
- references/call-scripts-pidgin.md 5.0 KB
- references/demo-mode.md 1.0 KB
- references/examples.md 2.5 KB
- references/result-schema-inventory.json 1.7 KB
- references/result-schema-onboarding.json 1.9 KB
- references/result-schema-order-status.json 1.2 KB
- references/result-schema-payment-consent.json 1.5 KB
- references/result-schema-reorder-offer.json 2.0 KB
- references/result-schema-sales.json 1.3 KB
- references/result-schema-vendor-order.json 1.5 KB
- references/safety.md 6.8 KB
- references/scheduling.md 7.4 KB
- scripts/render_schedule.py 6.5 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 200 lines · 46 tokens per session scan A 453ce16e545d
shop-voice-checkin is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 2,253 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-18.
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