Model Registry Logging

Organization

RedHatProductSecurity

model-registry-logging

Enforce centralized security logging for model registries. Use when building, configuring, or reviewing logging and audit capabilities of model registries.

Overview

Publisher	RedHatProductSecurity
Repository	`prodsec-skills`
Skill name	`model-registry-logging`
Stars	56
Forks	9
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by RedHatProductSecurity on GitHub. Read the source before you install it.

Installation

Install the Model Registry Logging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/RedHatProductSecurity/prodsec-skills/tree/main/module/skills/model-registry-logging
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/RedHatProductSecurity/prodsec-skills/tree/main/module/skills/model-registry-logging

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/RedHatProductSecurity/prodsec-skills.git /tmp/prodsec-skills
mkdir -p .claude/skills
cp -r /tmp/prodsec-skills/module/skills/model-registry-logging .claude/skills/model-registry-logging

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Model Registry Logging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Model Registry Logging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Model Registry Logging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Centralized Logging for Model Registries

Security Requirement

Model registry accesses, model uploads and downloads, and any security events MUST be sent to a centralized logging facility using standard protocols.

Events to Log

Event Category	Specific Events
Access events	User logins, API access, storage access
Model lifecycle	Model uploads, downloads, deletions, version changes
Security events	Signature verification failures, scanning results, access denials
Administrative events	Configuration changes, permission changes, user management
Anomalies	Unusual download patterns, access from unexpected sources

Logging Requirements

Requirement	Details
Centralized destination	All logs sent to a central logging facility (SIEM, ELK, Splunk)
Standard protocols	Use standard log shipping protocols (syslog, OTLP, Fluentd)
Structured format	Logs in structured format (JSON) with consistent field names
Identity included	Every log entry includes the authenticated principal's identity
Tamper protection	Logs should not be modifiable by the application or its operators
Retention	Log retention per organizational and regulatory requirements

Example Log Entry

json
{
  "timestamp": "2026-03-03T10:30:00Z",
  "event_type": "model.signature_verification_failed",
  "severity": "high",
  "principal": "pipeline:ci-model-upload",
  "model_id": "llama-3-fine-tuned-v2",
  "details": "Signature verification failed: unknown signing key",
  "source_ip": "10.0.1.50",
  "registry": "prod-model-registry"
}

Implementation Checklist

Configure centralized log destination (SIEM or logging platform)
Use standard log shipping protocol (syslog, OTLP, or equivalent)
Log all access events with authenticated principal identity
Log all model lifecycle events (upload, download, delete)
Log all security events (verification failures, scan results, access denials)
Use structured JSON format with consistent field names
Ensure log integrity (forward to tamper-protected storage)
Set log retention per organizational policy
Create alerts for high-severity security events

Frequently asked questions

What does the Model Registry Logging AI skill do?

Enforce centralized security logging for model registries. Use when building, configuring, or reviewing logging and audit capabilities of model registries.

Why use Model Registry Logging on TypingMind?

Because you install it once and use it with any model. Model Registry Logging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Model Registry Logging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RedHatProductSecurity/prodsec-skills/tree/main/module/skills/model-registry-logging. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Model Registry Logging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Model Registry Logging?

As many as you like. As long as a model supports skills, you can use Model Registry Logging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Model Registry Logging AI skill free?

Yes. It is published on GitHub by RedHatProductSecurity under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Centralized Logging for Model Registries

Security Requirement

Events to Log

Logging Requirements

Example Log Entry

Implementation Checklist

Frequently asked questions

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