api-telemetry

api-telemetry is a skill for Claude Code from huaqing0/obsidian-mcp-server. It costs 85 tokens per session (4,958 once invoked), scanned A, a copy of api-telemetry, Apache-2.0.

A reference for adding OpenTelemetry monitoring to an MCP server. OpenTelemetry is a standard for recording traces, measurements, and related logs so developers can see what the server is doing.

In plain words
What is it for?
Use it to enable monitoring exports, add custom traces or measurements, understand automatic instrumentation, investigate missing telemetry, and avoid overly detailed measurement labels.
Why use it?
It helps explain how requests and operations are tracked, including how logs connect to a particular request. It also covers configuration and common runtime limitations.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the obsidian-mcp-server plugin — 32 skills, 1 MCP server shipped together

Good fit Use it to enable monitoring exports, add custom traces or measurements, understand automatic instrumentation, investigate missing telemetry, and avoid overly detailed measurement labels.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/huaqing0/obsidian-mcp-server/api-telemetry
Install

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.

Any agent
npx skills add huaqing0/obsidian-mcp-server --skill api-telemetry
Clone the repo
git clone --depth 1 https://github.com/huaqing0/obsidian-mcp-server

Made for: Claude Code.

Or install obsidian-mcp-server, the plugin that ships this one along with the rest of its 32 skills, 1 MCP server.

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 api-telemetry

README.md
[![agentmods](https://agentmods.dev/badge/skills/huaqing0/obsidian-mcp-server/api-telemetry.svg)](https://agentmods.dev/skills/huaqing0/obsidian-mcp-server/api-telemetry)
Your own site
<a href="https://agentmods.dev/skills/huaqing0/obsidian-mcp-server/api-telemetry"><img src="https://agentmods.dev/badge/skills/huaqing0/obsidian-mcp-server/api-telemetry.svg" alt="Measured on agentmods" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,958 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 $0.00085 $0.04958
Opus 5 $0.00043 $0.02479
Sonnet 5 $0.00017 $0.00992
Haiku 4.5 $0.00009 $0.00496

Measured 8d ago against content hash bb656e39dd17, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

api-telemetry 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 8d 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 api-telemetry — 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.

skills/api-telemetry/SKILL.md · 253 lines

How it starts

The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

The framework auto-instruments every tool, resource, prompt, storage, LLM, speech, and graph call — each gets its own span and the standard counters/histograms. HTTP server requests pick up spans from HttpInstrumentation (all Node.js HTTP traffic, skips /healthz) plus httpInstrumentationMiddleware from @hono/otel on the MCP HTTP endpoint when installed (optional Tier 3 peer — bun add @hono/otel). On Bun, HttpInstrumentation silently no-ops and @hono/otel is the only HTTP coverage. Auth checks and session lifecycle are tracked as metrics only — auth decorates the active HTTP span with attributes, sessions emit counters.

requestId, traceId, and tenantId correlate automatically across spans, metrics, and logs. Pino logs get trace_id/span_id injected when a span is active.

A handler's ctx.traceId / ctx.spanId name the execution span it runs in — tool_execution:<name> or resource_read:<name> — not the enclosing HTTP request span. Under HTTP the trace ID is the request's, so handler logs join to the request; the span ID is the child execution's, so they join to that span's attributes and duration. On stdio, where no transport span exists, both are still populated from the execution span the framework opens. Both are undefined when telemetry is disabled: the non-recording span a disabled pipeline produces carries all-zero IDs, and the framework reports no correlation rather than IDs that correlate to nothing.

For the helper API surface (withSpan, createCounter, createHistogram, buildTraceparent, etc.) — see the api-utils skill, Telemetry section. This skill is the catalog of what is emitted; that one is the reference for how to emit your own.


Enabling export

OTel is off by default. OTEL_ENABLED=true alone does nothing — you also need an OTLP endpoint. Without an endpoint the SDK is configured but nothing leaves the process.

Env var Default Purpose
OTEL_ENABLED false Master switch. Must be true to start the SDK.
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT OTLP/HTTP traces endpoint (e.g. http://localhost:4318/v1/traces).
OTEL_EXPORTER_OTLP_METRICS_ENDPOINT OTLP/HTTP metrics endpoint (e.g. http://localhost:4318/v1/metrics).
OTEL_SERVICE_NAME createApp namepackage.json name service.name resource attribute. Seeded from createApp({ name }) when unset; an env value wins.
OTEL_SERVICE_VERSION package.json version service.version resource attribute.
OTEL_TRACES_SAMPLER_ARG 1.0 Trace sampling ratio (0–1) for TraceIdRatioBasedSampler.
OTEL_LOG_LEVEL INFO OTel diagnostic logger level (NONE/ERROR/WARN/INFO/DEBUG/VERBOSE/ALL).

Read the full file on GitHub · 253 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. 8d ago First seen · 253 lines · 85 tokens per session scan A bb656e39dd17

Subscribe to this mod's changes

api-telemetry is a skill published in the GitHub repository huaqing0/obsidian-mcp-server (0 stars, last pushed 12d ago), licensed Apache-2.0. It adds 85 tokens to every session and 4,958 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to api-telemetry, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens