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.
npx skills add MLOps-Courses/mlops-coding-skills --skill mlops-collaborationgit clone --depth 1 https://github.com/MLOps-Courses/mlops-coding-skillsWrote 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.
[](https://agentmods.dev/skills/mlops-courses/mlops-coding-skills/mlops-collaboration)<a href="https://agentmods.dev/skills/mlops-courses/mlops-coding-skills/mlops-collaboration"><img src="https://agentmods.dev/badge/skills/mlops-courses/mlops-coding-skills/mlops-collaboration/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.
<a href="https://agentmods.dev/skills/mlops-courses/mlops-coding-skills/mlops-collaboration"><img src="https://agentmods.dev/badge/skills/mlops-courses/mlops-coding-skills/mlops-collaboration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.01504 |
| Opus 5.5 | $0.00020 | $0.00602 |
| Sonnet 5.5 | $0.00010 | $0.00301 |
| Haiku 4.5 | $0.00005 | $0.00150 |
Grade A, and why
mlops-collaboration 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MLOps Collaboration
Goal
To prepare a repository for collaboration while preserving its requested visibility by establishing Governance (License, Code of Conduct, branch rulesets), Documentation (README, AGENTS, Contributing), Standardization (Templates, Workstations), and Release Management.
Prerequisites
- Language: Python 3.14
- Platform: GitHub
- Context: Open sourcing or team collaboration.
Instructions
Preserve existing work and repository visibility. Prepare local changes first; commit, push, change remote settings, publish, or deploy only with user authorization.
1. Repository Governance
Set the rules of engagement.
- License: Pick an SPDX identifier and commit the full text. Declare it in
pyproject.tomlaslicense = "MIT"pluslicense-files = ["LICENSE.txt"](PEP 639), and make sure the file itself carries its title and copyright line — a bare license body with noCopyright (c) <year> <author>is legally ambiguous. - Code of Conduct: Add
CODE_OF_CONDUCT.mdto foster a safe community. - Branch Protection (concretely): commit
.github/rulesets/main.jsonand apply it withmise run install:rulesets. A ruleset in the repository is reviewable, diffable, and restorable; a setting clicked in the web UI is none of those. A useful baseline blocks deletion and non-fast-forward pushes, requires linear history, requires a pull request, and requires the CI status check to pass.- Make the task idempotent: look the ruleset up by name and
PUTover it when it exists,POSTonly when it does not. A plainPOSTcreates a duplicate ruleset on every run. - The ruleset must match the check context reported by CI. A job
nameor matrix can change that context; verify the displayed check before requiring it.
- Make the task idempotent: look the ruleset up by name and
- Review: Automate preliminary reviews with tools like Gemini Code Assist (
.gemini/config.yaml). - Ignore: Comprehensive
.gitignore(exclude secrets, data, virtualenvs, and local MLflow state such asmlflow.dbandmlartifacts/).
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.
- 6d ago Changed · +2 lines 1dffb8261b30
- 1mo ago First seen · 79 lines · 50 tokens per session scan A 1ca655c2e24a
mlops-collaboration is a skill published in the GitHub repository MLOps-Courses/mlops-coding-skills (23 stars, last pushed 7d ago), licensed MIT. It adds 50 tokens to every session and 1,504 once invoked, about $0.0002 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 2026-08-30.
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github
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