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 team-telnyx/ai --skill telnyx-ai-outbound-voice-pythongit clone --depth 1 https://github.com/team-telnyx/aiWrote 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/team-telnyx/ai/telnyx-ai-outbound-voice-python)<a href="https://agentmods.dev/skills/team-telnyx/ai/telnyx-ai-outbound-voice-python"><img src="https://agentmods.dev/badge/skills/team-telnyx/ai/telnyx-ai-outbound-voice-python/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/team-telnyx/ai/telnyx-ai-outbound-voice-python"><img src="https://agentmods.dev/badge/skills/team-telnyx/ai/telnyx-ai-outbound-voice-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 8 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 98 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 122 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 128 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 135 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 230 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 236 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 238 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 243 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00097 | $0.02308 |
| Opus 5 | $0.00048 | $0.01154 |
| Sonnet 5 | $0.00019 | $0.00462 |
| Haiku 4.5 | $0.00010 | $0.00231 |
Grade A, and why
telnyx-ai-outbound-voice-python scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
r = requests.get( How it starts
The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telnyx AI Outbound Voice Calls - Python
Make an AI assistant call any phone number. This skill covers the complete setup from purchasing a number to triggering the call.
Installation
pip install telnyx requests
Setup
import os
from telnyx import Telnyx
client = Telnyx(api_key=os.environ.get("TELNYX_API_KEY"))
Prerequisites
Outbound voice calls require all of the following. Missing any one produces a specific error — see Troubleshooting.
- A purchased Telnyx phone number
- A TeXML application
- The phone number assigned to the TeXML application
- An outbound voice profile with destination countries whitelisted
- An AI assistant with
telephony_settings.default_texml_app_idset to the TeXML app
Model availability
Model availability varies by account. If client.ai.assistants.create() returns
422 "not available for inference", discover working models from existing assistants:
for a in client.ai.assistants.list().data:
print(a.model)
Commonly available: openai/gpt-4o, Qwen/Qwen3-235B-A22B.
Step 1: Purchase a phone number
import time
available = client.available_phone_numbers.list()
phone = available.data[0].phone_number
number_order = client.number_orders.create(
phone_numbers=[{"phone_number": phone}],
)
time.sleep(3)
order = client.number_orders.retrieve(number_order.data.id)
assert order.data.status == "success"
print(f"Purchased: {phone}")
Step 2: Create a TeXML application
The voice_url is required by the API but is not used for outbound AI assistant calls.
The TeXML app ID is also used as the connection_id when assigning phone numbers.
texml_app = client.texml_applications.create(
friendly_name="My AI Assistant App",
voice_url="https://example.com/placeholder",
)
app_id = texml_app.data.id # This is also the connection_id for phone number assignment
Step 3: Assign the phone number to the TeXML application
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.
- 4d ago First seen · 317 lines · 97 tokens per session scan A e8fff751ab42
telnyx-ai-outbound-voice-python is a skill published in the GitHub repository team-telnyx/ai (213 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 2,308 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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