Borrowing it
Nothing to install: this file belongs to pareelamre/analyzing-llm-rationale. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pareelamre/analyzing-llm-rationale/main/.agents/skills/otel-python-style/SKILL.mdgit clone --depth 1 https://github.com/pareelamre/analyzing-llm-rationaleWrote 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/pareelamre/analyzing-llm-rationale/otel-python-style)<a href="https://agentmods.dev/skills/pareelamre/analyzing-llm-rationale/otel-python-style"><img src="https://agentmods.dev/badge/skills/pareelamre/analyzing-llm-rationale/otel-python-style.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.00885 |
| Opus 5 | $0.00015 | $0.00443 |
| Sonnet 5 | $0.00006 | $0.00177 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
otel-python-style 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 6d 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
100% identical to otel-python-style — 0 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OTel Python Style
Acquire OTel objects at module scope.
from opentelemetry import metrics, trace
from opentelemetry.trace import Status, StatusCode
tracer = trace.get_tracer("mugline.voice")
meter = metrics.get_meter("mugline.voice")
greetings = meter.create_counter("voice.greetings.delivered", unit="1")
Bounded Work
tracer.start_as_current_span(...) works as both a decorator and a context
manager — the same call. For a whole function, the decorator form is usually
what you want:
@tracer.start_as_current_span("do_work")
def do_work():
print("doing some work...")
It works the same way on async functions and on methods, and you can grab the
active span inside the body with trace.get_current_span() to set attributes:
@tracer.start_as_current_span("voice.deliver_initial_greeting")
async def _deliver_initial_greeting(*, tenant_id: str, user_id: str) -> None:
span = trace.get_current_span()
span.set_attributes({
"tenant.id": tenant_id,
"user.id": user_id,
"voice.use_case": "initial_greeting",
})
Use a context manager when a decorator does not fit (partial scope, dynamic span name, etc.).
with tracer.start_as_current_span("order.validate") as span:
span.set_attribute("tenant.id", tenant_id)
validate_order(order)
Do not use detached tracer.start_span(...); span.end() for bounded work.
Error Paths
Record exceptions on the active span.
try:
result = await client.messages.create(...)
except Exception as exc:
span = trace.get_current_span()
span.record_exception(exc)
span.set_status(Status(StatusCode.ERROR))
logger.exception("llm mug copy failed", extra={"tenant_id": tenant_id})
raise
Logs
If logs are claimed as OTLP-forwarded, configure both:
- an OTel LoggerProvider + OTLPLogExporter + LoggingHandler
set_logger_provider(logger_provider)fromopentelemetry._logs- log correlation for existing records, e.g.
LoggingInstrumentor().instrument(...)
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.
- 6d ago First seen · 132 lines · 31 tokens per session scan A dc2d8cd8109c
otel-python-style is a skill published in the GitHub repository pareelamre/analyzing-llm-rationale (0 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 885 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to otel-python-style, differing in 0 lines, and is treated as a copy.
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