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Metrics Server

DevOps & Security
metrics-server

Metrics Server is an Agent Skill for devops & security published in the Mesh-LLM/mesh-llm repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Use this skill when working on benchmark telemetry ingest, metrics-server run lifecycle, OTLP collection, SQLite storage, benchmark report export, or separating telemetry/reporting ownership from staged runtime servers.

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/Mesh-LLM/mesh-llm/blob/HEAD/.agents/skills/metrics-server/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/metrics-server, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

metrics-server

Use this skill when working on benchmark telemetry ingest, run lifecycle, or report export.

Commands

cargo build -p metrics-server

target/debug/metrics-server serve \
  --db /tmp/metrics.sqlite \
  --http-addr 127.0.0.1:18080 \
  --otlp-grpc-addr 127.0.0.1:14317

Benchmark reports should come from metrics-server data. Stage servers emit OTLP; they do not own canonical report export.

Workflow

  • Start metrics-server before a benchmark or experimental skippy run.
  • Pass the OTLP endpoint to skippy stages with --metrics-otlp-grpc.
  • Use --debug-retain-raw-otlp only for surgical debugging; default reports should avoid retaining raw payloads.
  • Finalize the run through the HTTP API and export report.json from metrics-server data.