analyzing-llm-rationale: Skill for Claude Code

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

otel-nextjs-style is a skill for Claude Code, Codex from pareelamre/analyzing-llm-rationale. It costs 46 tokens per session (1,383 once invoked), scanned A, a copy of otel-nextjs-style, MIT.

A coding guide for adding OpenTelemetry monitoring to Next.js and Vercel applications. It covers the framework's startup file and monitoring of language-model providers such as Anthropic.

In plain words
What is it for?
Use it when setting up traces and logs in a Next.js app, configuring the public ingest token, or connecting Anthropic monitoring.
Why use it?
It avoids replacing Next.js's normal startup process with a custom one that may not fit the framework. It also helps capture language-model activity while keeping application code readable.

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-nextjs-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-nextjs-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-nextjs-style

Your own site · 80×15
<a href="https://agentmods.dev/skills/pareelamre/analyzing-llm-rationale/otel-nextjs-style"><img src="https://agentmods.dev/badge/skills/pareelamre/analyzing-llm-rationale/otel-nextjs-style.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,383 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 $0.00046 $0.01383
Opus 5 $0.00023 $0.00691
Sonnet 5 $0.00009 $0.00277
Haiku 4.5 $0.00005 $0.00138

Measured 11d ago against content hash 7319d31fd5cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

otel-nextjs-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 11d 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-nextjs-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-nextjs-style/SKILL.md · 152 lines

How it starts

The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OTel Next.js Style

For Next.js apps, prefer the framework entrypoint.

// instrumentation.ts
import { registerOTel } from "@vercel/otel";

export function register() {
  registerOTel({
    serviceName: "mugline-web",
  });
}

Do not replace this with a custom NodeSDK bootstrap unless the repo is not a normal Next/Vercel app or already has a custom provider that must be extended.

For JavaScript/TypeScript LLM providers, prefer provider instrumentation over manual child spans. For Anthropic, add OpenInference in the same bootstrap and keep call sites native. This example uses @vercel/[email protected]; if the installed types are v1, use logRecordProcessor singular instead.

import Anthropic from "@anthropic-ai/sdk";
import { AnthropicInstrumentation } from "@arizeai/openinference-instrumentation-anthropic";
import { OTLPLogExporter } from "@opentelemetry/exporter-logs-otlp-http";
import { BatchLogRecordProcessor } from "@opentelemetry/sdk-logs";
import { registerOTel } from "@vercel/otel";

const anthropicInstrumentation = new AnthropicInstrumentation({
  traceConfig: {
    hideInputs: true,
    hideOutputs: true,
  },
});

anthropicInstrumentation.manuallyInstrument(Anthropic);

export function register() {
  registerOTel({
    serviceName: "mugline-web",
    instrumentations: [anthropicInstrumentation],
    logRecordProcessors: [new BatchLogRecordProcessor(new OTLPLogExporter())],
  });
}

Route Handlers

Use native OTel APIs where auto-instrumentation is blind.

import { withSpan } from "@superlog/otel-helpers";

const tracer = trace.getTracer("mugline.web");
const meter = metrics.getMeter("mugline.web");
const requests = meter.createCounter("mug.copy.generated");

export async function POST(request: Request) {
  const tenantId = request.headers.get("x-tenant-id") ?? "tenant_demo";
  return await withSpan("mug.copy.generate", async (span) => {
    span.setAttribute("tenant.id", tenantId);
    requests.add(1, { "tenant.id": tenantId, outcome: "success" });
    return Response.json({ ok: true });
  }, { tracer });
}

Read the full file on GitHub · 152 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. 11d ago First seen · 152 lines · 46 tokens per session scan A 7319d31fd5cb

Subscribe to this mod's changes

otel-nextjs-style is a skill published in the GitHub repository pareelamre/analyzing-llm-rationale (0 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 1,383 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-nextjs-style, differing in 0 lines, and is treated as a copy.

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