analyzing-llm-rationale: Skill for Claude Code

.agents/skills/otel-python-style/SKILL.md

otel-python-style is a skill for Claude Code, Codex from pareelamre/analyzing-llm-rationale. It costs 31 tokens per session (885 once invoked), scanned A, a copy of otel-python-style, MIT.

A Python coding guide for adding OpenTelemetry monitoring to functions and methods. It covers traces, measurements, logs, and recording errors.

In plain words
What is it for?
Use it when instrumenting Python services to measure operations, attach details to active traces, record errors, and create counters.
Why use it?
It shows how to monitor normal and asynchronous Python work without building custom wrappers. This makes it easier to see what a function did and whether it failed.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is pareelamre/analyzing-llm-rationale's own configuration. It tells Claude Code and Codex how to work on analyzing-llm-rationale itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything analyzing-llm-rationale configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/pareelamre/analyzing-llm-rationale/main/.agents/skills/otel-python-style/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/pareelamre/analyzing-llm-rationale

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for otel-python-style

README.md
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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.

agentmods 80×15 button for otel-python-style

Your own site · 80×15
<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="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 885 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.00885
Opus 5.5 $0.00012 $0.00354
Sonnet 5.5 $0.00006 $0.00177
Haiku 4.5 $0.00003 $0.00089

Measured 2mo ago against content hash dc2d8cd8109c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

Origin

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.

.agents/skills/otel-python-style/SKILL.md · 132 lines

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) from opentelemetry._logs
  • log correlation for existing records, e.g. LoggingInstrumentor().instrument(...)

Read the full file on GitHub · 132 lines

Changes

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.

  1. 2mo ago First seen · 132 lines · 31 tokens per session scan A dc2d8cd8109c

Subscribe to this mod's changes

otel-python-style is a skill published in the GitHub repository pareelamre/analyzing-llm-rationale (0 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 885 once invoked, about $0.0001 per session on Opus 5.5. 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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