mlops-engineer

mlops-engineer is an agent for Claude Code from josstei/maestro-orchestrate. It costs 271 tokens per session (396 once invoked), scanned A, original, Apache-2.0.

An MLOps specialist for operating machine-learning models after they are built. MLOps is the practice of packaging, deploying, monitoring, and updating models through automated software processes.

In plain words
What is it for?
Use it to set up model registries, model CI/CD pipelines, serving packages, drift monitoring, scheduled retraining, and canary rollouts.
Why use it?
It helps connect model training with reliable delivery and ongoing monitoring. This reduces manual deployment work and helps detect when a model's results or data have changed over time.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the maestro plugin — 19 skills, 33 agents, 1 MCP server shipped together

Good fit Use it to set up model registries, model CI/CD pipelines, serving packages, drift monitoring, scheduled retraining, and canary rollouts.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/josstei/maestro-orchestrate/mlops-engineer
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.

Clone the repo
git clone --depth 1 https://github.com/josstei/maestro-orchestrate

Made for: Claude Code.

Or install maestro, the plugin that ships this one along with the rest of its 19 skills, 33 agents, 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 mlops-engineer

README.md
[![agentmods](https://agentmods.dev/badge/agents/josstei/maestro-orchestrate/mlops-engineer/github.svg)](https://agentmods.dev/agents/josstei/maestro-orchestrate/mlops-engineer)
Your own site
<a href="https://agentmods.dev/agents/josstei/maestro-orchestrate/mlops-engineer"><img src="https://agentmods.dev/badge/agents/josstei/maestro-orchestrate/mlops-engineer/github.svg" alt="Measured on agentmods" height="20"></a>

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 mlops-engineer

Your own site · 80×15
<a href="https://agentmods.dev/agents/josstei/maestro-orchestrate/mlops-engineer"><img src="https://agentmods.dev/badge/agents/josstei/maestro-orchestrate/mlops-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 271 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 396 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 original No closer match found 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 $0.00271 $0.00396
Opus 5.5 $0.00108 $0.00158
Sonnet 5.5 $0.00054 $0.00079
Haiku 4.5 $0.00027 $0.00040

Measured yesterday against content hash 0fcda7aa7e1c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

mlops-engineer 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 yesterday.

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.

claude/agents/mlops-engineer.md · 40 lines

What it actually says

Agent methodology loaded via MCP tool get_agent. Call get_agent(agents: ["mlops-engineer"]) to read the full methodology at delegation time.

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. yesterday First seen · 40 lines · 271 tokens per session scan A 0fcda7aa7e1c

Subscribe to this mod's changes

mlops-engineer is an agent published in the GitHub repository josstei/maestro-orchestrate (465 stars, last pushed yesterday), licensed Apache-2.0. It adds 271 tokens to every session and 396 once invoked, about $0.0011 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-07.

Related

Other agents, from other repositories

devops-engineer

Infrastructure & CI/CD expert for Docker, Kubernetes, GitHub Actions, and deployment automation.

nth5693/gemini-kit · 23 tokens

workflow-subagent

Generic stage executor for the stagent plugin. Launched by the main agent for any subagent-typed stage in a workflow. Self-resolves its stage context from state.md via subagent-bootstrap.sh — does NOT rely on the main agent's prompt for path / epoch / input data. Then follows the stage's canonical instructions file…

jie-worldstatelabs/stagent · 91 tokens

pytorch-build-resolver

PyTorch runtime, CUDA, and training error resolution specialist. Fixes tensor shape mismatches, device errors, gradient issues, DataLoader problems, and mixed precision failures with minimal changes. Use when PyTorch training or inference crashes.

Jamkris/everything-gemini-code · 52 tokens

security-auditor

Expert security auditor specializing in DevSecOps, comprehensive cybersecurity, and compliance frameworks. Masters vulnerability assessment, threat modeling, secure authentication (OAuth2/OIDC), OWASP standards, cloud security, and security automation. Handles DevSecOps integration, compliance (GDPR/HIPAA/SOC2), and…

HermeticOrmus/LibreUIUX-Claude-Code · 85 tokens

workflow-engineer

GitHub workflow engineer for issue-driven delivery, PR follow-through, CI failure triage, review readiness, host drift, and task-memory closeout.

45ck/skill-harness · 34 tokens

the-translator

Use when converting technical AI results (eval metrics, latency numbers, failure modes, model trade-offs) into business language for executives, stakeholders, or investor demos. Trigger for demo prep, exec summaries, post-incident comms, or when an AI-technical result must land with a non-technical audience. Distinct…

shrwnsan/vibekit-claude-plugins · 95 tokens