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 benjaminasterA/antigravity-awesome-skills --skill azure-monitor-opentelemetry-pygit clone --depth 1 https://github.com/benjaminasterA/antigravity-awesome-skillsWrote 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/benjaminastera/antigravity-awesome-skills/azure-monitor-opentelemetry-py)<a href="https://agentmods.dev/skills/benjaminastera/antigravity-awesome-skills/azure-monitor-opentelemetry-py"><img src="https://agentmods.dev/badge/skills/benjaminastera/antigravity-awesome-skills/azure-monitor-opentelemetry-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/benjaminastera/antigravity-awesome-skills/azure-monitor-opentelemetry-py"><img src="https://agentmods.dev/badge/skills/benjaminastera/antigravity-awesome-skills/azure-monitor-opentelemetry-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.01172 |
| Opus 5 | $0.00000 | $0.00586 |
| Sonnet 5 | $0.00000 | $0.00234 |
| Haiku 4.5 | $0.00000 | $0.00117 |
Grade A, and why
azure-monitor-opentelemetry-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 9d 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Monitor OpenTelemetry Distro for Python
One-line setup for Application Insights with OpenTelemetry auto-instrumentation.
Installation
pip install azure-monitor-opentelemetry
Environment Variables
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/
Quick Start
from azure.monitor.opentelemetry import configure_azure_monitor
# One-line setup - reads connection string from environment
configure_azure_monitor()
# Your application code...
Explicit Configuration
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor(
connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/"
)
With Flask
from flask import Flask
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
app = Flask(__name__)
@app.route("/")
def hello():
return "Hello, World!"
if __name__ == "__main__":
app.run()
With Django
# settings.py
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
# Django settings...
With FastAPI
from fastapi import FastAPI
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
app = FastAPI()
@app.get("/")
async def root():
return {"message": "Hello World"}
Custom Traces
from opentelemetry import trace
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("my-operation") as span:
span.set_attribute("custom.attribute", "value")
# Do work...
Custom Metrics
from opentelemetry import metrics
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
meter = metrics.get_meter(__name__)
counter = meter.create_counter("my_counter")
counter.add(1, {"dimension": "value"})
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.
- 9d ago First seen · 230 lines · 0 tokens per session scan A 070f0703ca3d
azure-monitor-opentelemetry-py is a skill published in the GitHub repository benjaminasterA/antigravity-awesome-skills (271 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,172 tokens. 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 2026-09-03.
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