telemetry — embeddings telemetry, community, embeddings, ide skills, frontmatter, markdown, parquet, semantic-search, validation, word2vec, Claude Code

v1.0.0

이 스킬 정보

Rust와 Word2Vec를 사용하는 마크다운 디렉토리의 고급 원격 측정 기능이 필요한 AI 에이전트에게 적합합니다. Telemetry and observability conventions. Apply when adding tracing, logging, metrics, or instrumentation to Rust code.

# Core Topics

edochi edochi
[1]
[0]
Updated: 3/17/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
7/11
Quality Score
33
Canonical Locale
en
Detected Body Locale
en

Rust와 Word2Vec를 사용하는 마크다운 디렉토리의 고급 원격 측정 기능이 필요한 AI 에이전트에게 적합합니다. Telemetry and observability conventions. Apply when adding tracing, logging, metrics, or instrumentation to Rust code.

이 스킬을 사용하는 이유

스키마 추론, 프론트매터 유효성 검사 및 의미 검색을 수행할 수 있는 기능을 에이전트에 부여하여 Rust 및 Word2Vec와 같은 기술을 사용하여 포괄적인 콘텐츠 분석을 수행하고 오류, 경고, 정보 수준을 사용하여 강력한 원격 측정 및 관찰 가능성을 구현합니다.

최적의 용도

Rust와 Word2Vec를 사용하는 마크다운 디렉토리의 고급 원격 측정 기능이 필요한 AI 에이전트에게 적합합니다.

실행 가능한 사용 사례 for telemetry

마크다운 디렉토리에서 스키마 추론을 수행한다
일관성 및 정확성을 보장하기 위해 프론트매터를 검증한다
효율적인 콘텐츠 검색을 위해 의미 검색을 수행한다

! 보안 및 제한 사항

  • 전용 원격 측정/관찰 가능성 사양 또는 규약 문서가 필요하다
  • 마크다운 디렉토리에만 제한된다
  • Rust 및 Word2Vec와 같은 기술에 의존한다

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is telemetry?

Rust와 Word2Vec를 사용하는 마크다운 디렉토리의 고급 원격 측정 기능이 필요한 AI 에이전트에게 적합합니다. Telemetry and observability conventions. Apply when adding tracing, logging, metrics, or instrumentation to Rust code.

How do I install telemetry?

Run the command: npx killer-skills add edochi/mdvs/telemetry. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for telemetry?

Key use cases include: 마크다운 디렉토리에서 스키마 추론을 수행한다, 일관성 및 정확성을 보장하기 위해 프론트매터를 검증한다, 효율적인 콘텐츠 검색을 위해 의미 검색을 수행한다.

Which IDEs are compatible with telemetry?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for telemetry?

전용 원격 측정/관찰 가능성 사양 또는 규약 문서가 필요하다. 마크다운 디렉토리에만 제한된다. Rust 및 Word2Vec와 같은 기술에 의존한다.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add edochi/mdvs/telemetry. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use telemetry immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

telemetry

Install telemetry, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
Supporting Evidence

Telemetry & Observability Conventions

If the project has a dedicated telemetry/observability spec or conventions document, read it first — it takes precedence over the generic guidance below.

Log Levels

LevelWhen to UseExample
error!Unrecoverable failures requiring operator attentionExternal service call failed permanently
warn!Recoverable issues, degraded operationRetry triggered, fallback activated
info!Lifecycle events, operational milestonesServer started, connection established
debug!Internal state useful during developmentState machine transition details
trace!Per-frame, hot-path data (high volume)Frame encoded, bytes serialized

Instrumentation Depth

Not all code deserves the same instrumentation level. Choose based on the crate's role:

  • Hot-path code (serialization, framing, tight loops): trace! only, no spans. Spans add overhead that matters here.
  • Type definition crates (pure data types, no logic): trace! only if anything at all.
  • Core business logic (servers, handlers, state machines): Full instrumentation — #[instrument] + spans.
  • Client-facing code (SDKs, CLI flows): Full instrumentation for debuggability.

#[instrument] Rules

  • Use on async functions that represent logical operations or flow steps
  • Skip on hot-path synchronous functions (serialization, encoding, tight loops)
  • Always skip sensitive fields: tokens, keys, passwords, raw payloads
  • Include identifying fields that aid correlation (IDs, resource names)
  • Set appropriate level — default is INFO, use level = "debug" or level = "trace" for noisy functions

Structured Logging

Always use named fields, never string interpolation:

rust
1// Good: named fields — searchable, parseable 2trace!(payload_bytes = payload.len(), frame_bytes = buf.len(), "frame encoded"); 3 4// Bad: string interpolation — opaque to log aggregators 5trace!("frame encoded, payload={}, frame={}", payload.len(), buf.len());

Span Design

For request/message processing pipelines, use a three-tier span pattern:

  • Inbound span: one per received message/request (message type, size, sender ID)
  • Process span: business logic processing (operation type, affected resources)
  • Outbound span: one per response/forwarded message (recipient, payload size)

This gives visibility into where time is spent and enables per-hop latency analysis.

General Principles

  • Prefer tracing over log — structured spans enable distributed tracing
  • Log at the point of decision, not at every intermediate step
  • Include enough context to diagnose without reproducing: IDs, sizes, error details
  • Never log secrets, tokens, keys, or raw user data — even at trace! level
  • Use Display for user-facing context, Debug for developer diagnostics

관련 스킬

Looking for an alternative to telemetry or another community skill for your workflow? Explore these related open-source skills.

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