ZenML is a Python framework for turning machine-learning and AI workflows into tracked pipelines that run on different infrastructure backends. It is for ML and AI engineers building applications such as model-training workflows, language-model systems, and agent loops in company environments.
Borrowing it
Nothing to install: this file belongs to zenml-io/zenml. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zenml-io/zenml/main/.claude/settings.jsongit clone --depth 1 https://github.com/zenml-io/zenmlWrote 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/settings/zenml-io/zenml/settings)<a href="https://agentmods.dev/settings/zenml-io/zenml/settings"><img src="https://agentmods.dev/badge/settings/zenml-io/zenml/settings/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/settings/zenml-io/zenml/settings"><img src="https://agentmods.dev/badge/settings/zenml-io/zenml/settings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
zenml 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 14d 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.
What it actually says
{
"$schema": "https://json.schemastore.org/claude-code-settings.json",
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "if jq -r '.tool_input.command' 2>/dev/null | grep -q 'git commit'; then echo '🔍 Running pre-commit formatting...'; bash \"$CLAUDE_PROJECT_DIR\"/scripts/format.sh && echo '✅ Formatting complete' || { echo '❌ Formatting failed - commit blocked' >&2; exit 2; }; fi",
"timeout": 300
}
]
}
]
}
}
What else settings.json configures
This page is one entry in a file that holds 2. Installing the file brings all of them; each is measured and scanned on its own page.
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.
- 14d ago Changed ab389ca62852
- 2mo ago First seen · 18 lines scan A 34456e365049
zenml is a settings file published in the GitHub repository zenml-io/zenml (5,629 stars, last pushed yesterday), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. 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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claude-code-best-practice
Agent settings declaring 30 hook events (PreToolUse, PermissionRequest, PostToolUse, PostToolUseFailure) and 24 allowed tools.