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 lesson-language-phone-practicegit 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/lesson-language-phone-practice)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/lesson-language-phone-practice"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/lesson-language-phone-practice/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/lesson-language-phone-practice"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/lesson-language-phone-practice.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 | $0.00040 | $0.01356 |
| Opus 5.5 | $0.00016 | $0.00542 |
| Sonnet 5.5 | $0.00008 | $0.00271 |
| Haiku 4.5 | $0.00004 | $0.00136 |
Grade A, and why
lesson-language-phone-practice 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lesson Language Phone Practice
Create one target-language phone role-play from a completed lesson, aiming for about 30 seconds and ending by 60 seconds. Default to preview only. Do not place a live call unless learner consent, destination, exact call plan, provider readiness, and one-call approval are all explicit in the current workflow.
Read references/safety.md before preparing any live path. Read references/examples.md when shaping a preview or interpreting a result.
Required inputs
Require all of these from an authoritative lesson or trainer-owned record:
- completed lesson/activity reference;
- lesson aim, stage aim, Can-do objective, and grammar target;
- one scenario; the lesson-plan phrases themselves are the narrow communication goals and assessment targets;
- two or three exact taught phrases selected from the lesson record;
- optional learner support or caller wording;
- trainer note or observed practice need;
- learner consent covering an AI call and transcript/result handling;
- one authorized E.164 destination, its supported region, and locale;
- a configured phone provider whose credentials stay in the host secret store.
Do not invent taught phrases, use unrelated learner data, scrape a number, infer a country code, or accept a browser/client result as evidence.
Workflow
- Freeze a preview containing the lesson reference, aims, Can-do, grammar, scenario, exact lesson-plan phrases, support, roughly 30-second target, 60-second maximum, one opportunity per phrase, and at most one contextual repair. Never ask the teacher to invent or replace assessment phrases in the phone task.
- Show the complete generated brief and success conditions to the trainer. Permit edits to the scenario, fixed facts and learner support, but never to provenance, lesson-plan phrases, call aims or phrase-derived success evidence. Require explicit trainer approval before assignment.
- Validate the destination against canonical E.164: a plus sign followed by a nonzero country code and 8–15 digits total. Validate region and locale against the provider's current supported list. Mask the destination in output, for example
+1415•••0100. - Confirm the learner explicitly consented to this purpose, destination, AI caller, timing, and transcript/result retention. One lesson or earlier call does not imply consent now.
- Produce the dry-run preview. State clearly: No call has been placed.
- Before live dispatch, show the exact masked recipient, purpose, phrases, provider, timing, data handling, one-call rule, and disable behavior. Wait for fresh approval for exactly one call.
- Reserve a durable operation before calling. Derive one stable idempotency key from the lesson-practice authorization, not a click, timestamp, retry counter, or random value. Persist the provider call ID immediately when returned.
- Submit once. A timeout, restart, ambiguous response, failure, voicemail, wrong person, or no answer never authorizes a new key or redial. Recover only the same operation through documented idempotent replay or the stored call ID.
- Poll the stored call ID to a documented terminal state. Do not treat provider task completion as proof that the language goal was demonstrated.
- Reconcile structured output against speaker-labelled transcript turns. Only learner speech may support phrase use or appropriateness. Unknown speakers, missing transcript, unsupported phrases, out-of-window duration, or ambiguous endpoint must return insufficient evidence.
- Return the bounded result and masked operation summary. Do not turn it into a generic score, proficiency level, mastery claim, credential, reward, readiness decision, or progression change.
What ships with it
2 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.
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 · 90 lines · 40 tokens per session scan A c375f5caa413
lesson-language-phone-practice is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 1,356 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 2026-09-15.
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