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 Ghosteken/agent-harness --skill azure-ai-translation-text-pygit clone --depth 1 https://github.com/Ghosteken/agent-harnessWrote 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/ghosteken/agent-harness/azure-ai-translation-text-py)<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-ai-translation-text-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-ai-translation-text-py/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/ghosteken/agent-harness/azure-ai-translation-text-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-ai-translation-text-py.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 | $0.00037 | $0.01706 |
| Opus 5.5 | $0.00015 | $0.00682 |
| Sonnet 5.5 | $0.00007 | $0.00341 |
| Haiku 4.5 | $0.00004 | $0.00171 |
Grade A, and why
azure-ai-translation-text-py 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.
This is a copy
88% identical to azure-ai-translation-text-py — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure AI Text Translation SDK for Python
Client library for Azure AI Translator text translation service for real-time text translation, transliteration, and language operations.
Installation
pip install azure-ai-translation-text
Environment Variables
AZURE_TRANSLATOR_KEY=<your-api-key>
AZURE_TRANSLATOR_REGION=<your-region> # e.g., eastus, westus2
# Or use custom endpoint
AZURE_TRANSLATOR_ENDPOINT=https://<resource>.cognitiveservices.azure.com
Authentication
API Key with Region
import os
from azure.ai.translation.text import TextTranslationClient
from azure.core.credentials import AzureKeyCredential
key = os.environ["AZURE_TRANSLATOR_KEY"]
region = os.environ["AZURE_TRANSLATOR_REGION"]
# Create credential with region
credential = AzureKeyCredential(key)
client = TextTranslationClient(credential=credential, region=region)
API Key with Custom Endpoint
endpoint = os.environ["AZURE_TRANSLATOR_ENDPOINT"]
client = TextTranslationClient(
credential=AzureKeyCredential(key),
endpoint=endpoint
)
Entra ID (Recommended)
from azure.ai.translation.text import TextTranslationClient
from azure.identity import DefaultAzureCredential
client = TextTranslationClient(
credential=DefaultAzureCredential(),
endpoint=os.environ["AZURE_TRANSLATOR_ENDPOINT"]
)
Basic Translation
# Translate to a single language
result = client.translate(
body=["Hello, how are you?", "Welcome to Azure!"],
to=["es"] # Spanish
)
for item in result:
for translation in item.translations:
print(f"Translated: {translation.text}")
print(f"Target language: {translation.to}")
Translate to Multiple Languages
result = client.translate(
body=["Hello, world!"],
to=["es", "fr", "de", "ja"] # Spanish, French, German, Japanese
)
for item in result:
print(f"Source: {item.detected_language.language if item.detected_language else 'unknown'}")
for translation in item.translations:
print(f" {translation.to}: {translation.text}")
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 · 283 lines · 37 tokens per session scan A d94791882981
azure-ai-translation-text-py is a skill published in the GitHub repository Ghosteken/agent-harness (4 stars, last pushed yesterday), licensed MIT. It adds 37 tokens to every session and 1,706 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to azure-ai-translation-text-py, differing in 11 lines, and is treated as a copy.
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