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Agent skill

Skippy Metrics

by Mesh-LLM in Mesh-LLM/mesh-llm

A skill your agent uses when working on skippy telemetry attributes, OTLP emission, benchmark metric names, runtime lifecycle telemetry, or separating telemetry/reporting ownership from stage…

Apache-2.0Auto-check passedAI & LLM Engineering

Install Skippy Metrics

skills CLI
$ npx skills add Mesh-LLM/mesh-llm --skill skippy-metrics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Mesh-LLM/mesh-llm skippy-metrics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/skippy-metrics .claude/skills/skippy-metrics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skippy-metrics
GitHub stars
3.5k
Token cost
~272 tokens
SKILL.md length
85 words
Files
1
Skills in repo
25
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when working on skippy telemetry attributes, OTLP emission, benchmark metric names, runtime lifecycle telemetry, or separating telemetry/reporting ownership from stage…

  • Working on skippy telemetry attributes
  • SKILL.md covers Ownership and Validation
  • Calls cargo
  • Benchmark metric names

What it does

Skippy Metrics is an agent skill from Mesh-LLM/mesh-llm. Use this skill when working on skippy telemetry attributes, OTLP emission, benchmark metric names, runtime lifecycle telemetry, or separating telemetry/reporting ownership from stage runtime serving.

Its SKILL.md is about 270 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering. It works with OpenTelemetry. The repository describes itself as: Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat. The licence is Apache-2.0.

When your agent uses it

  • Working on skippy telemetry attributes
  • Benchmark metric names
  • Runtime lifecycle telemetry
  • Separating telemetry/reporting ownership from stage runtime serving

Example prompts

  • “/skippy-metrics”

What it can do on your machine

Read from SKILL.md and the folder at commit 1b9f0cf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • cargo

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skippy Metrics loads about 272 tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 85 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~272

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Mesh-LLM/mesh-llm at commit 1b9f0cf, republished under its Apache-2.0 licence (© Mesh-LLM). 85 words, ~272 tokens.

Download SKILL.mdSave it as .claude/skills/skippy-metrics/SKILL.md (or your agent's skills folder).
name
skippy-metrics
description
Use this skill when working on skippy telemetry attributes, OTLP emission, benchmark metric names, runtime lifecycle telemetry, or separating telemetry/reporting ownership from stage runtime serving.
metadata.short-description
Work on skippy telemetry

skippy-metrics

Use this skill for telemetry attributes, lifecycle instrumentation, and benchmark/report integration.

Ownership

skippy/crates/skippy-metrics owns shared attribute names. Stage servers may emit OTLP/telemetry, but request-path serving must not block on telemetry export. skippy/crates/metrics-server owns benchmark/debug telemetry ingest, SQLite storage, run lifecycle, and canonical report export.

Mesh API runtime status is not a telemetry dump. Keep public runtime status backend-neutral and stable; expose backend details only when intentionally part of the status shape.

Validation

bash
cargo test -p skippy-serving --lib
cargo test -p mesh-llm --lib

Keep canonical benchmark report export in metrics-server rather than inside stage serving.

© Mesh-LLM, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/skippy-metrics of Mesh-LLM/mesh-llm.

Open the folder on GitHubat commit 1b9f0cf

Compare with similar skills

Skippy Metrics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skippy Metrics compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skippy Metrics this skillMesh-LLM/mesh-llm3.5k—~272Automated safety check: PassApache-2.0
Evalagentevals-dev/agentevals163—~904Automated safety check: PassApache-2.0
Phoenix LLM ObservabilityOrchestra-Research/AI-Research-SKILLs13k2 repos~2.9kAutomated safety check: PassMIT
Dt Obs GenaiDynatrace/dynatrace-for-ai163—~4.5kAutomated safety check: PassApache-2.0
Sentry Elixir SDKgetsentry/sentry-for-ai268—~3.5kAutomated safety check: PassApache-2.0
Logfire Evalspydantic/skills140—~3.6kAutomated safety check: PassMIT

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Works with

Categories

Questions about Skippy Metrics

What does Skippy Metrics do?

A skill your agent uses when working on skippy telemetry attributes, OTLP emission, benchmark metric names, runtime lifecycle telemetry, or separating telemetry/reporting ownership from stage…. Skippy Metrics is an agent skill from Mesh-LLM/mesh-llm. Use this skill when working on skippy telemetry attributes, OTLP emission, benchmark metric names, runtime lifecycle telemetry, or separating telemetry/reporting ownership from stage runtime serving.

When should I use Skippy Metrics?

Skippy Metrics fits situations like: working on skippy telemetry attributes; benchmark metric names; runtime lifecycle telemetry; separating telemetry/reporting ownership from stage runtime serving.

How do I install Skippy Metrics in Claude Code?

Run `npx skills add Mesh-LLM/mesh-llm --skill skippy-metrics -a claude-code`. Or copy the skill folder (.agents/skills/skippy-metrics in Mesh-LLM/mesh-llm) into .claude/skills/skippy-metrics in your project. Claude Code loads it when a task matches its description.

How do I install Skippy Metrics in Codex?

Run `npx skills add Mesh-LLM/mesh-llm --skill skippy-metrics -a codex`. Or copy the skill folder (.agents/skills/skippy-metrics in Mesh-LLM/mesh-llm) into .agents/skills/skippy-metrics in your project. Codex loads it when a task matches its description.

Can I use Skippy Metrics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Mesh-LLM/mesh-llm --skill skippy-metrics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skippy-metrics, .gemini/skills/skippy-metrics, .github/skills/skippy-metrics and .opencode/skills/skippy-metrics in your project.

What does Skippy Metrics need to run?

Going by SKILL.md and its folder, Skippy Metrics needs the command-line tools its instructions call (cargo).

Does Skippy Metrics access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skippy Metrics safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Skippy Metrics use?

Skippy Metrics is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skippy Metrics use?

About 272 tokens (SKILL.md is roughly 1.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Skippy Metrics?

Skills that share tags, products or a category with Skippy Metrics: Eval (agentevals-dev/agentevals, 163 stars), Phoenix LLM Observability (Orchestra-Research/AI-Research-SKILLs, 13k stars), Dt Obs Genai (Dynatrace/dynatrace-for-ai, 163 stars) and Sentry Elixir SDK (getsentry/sentry-for-ai, 268 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skippy Metrics?

Mesh-LLM (a GitHub organization) maintains it in Mesh-LLM/mesh-llm, which has 3,495 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 11, 2026.

Source: Mesh-LLM/mesh-llm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.