About this skill
A reusable Coding skill centered on Large Language Models Security Specialist. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.
Use this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A reusable Coding skill centered on Large Language Models Security Specialist. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.
Load metadata first, then read the body and bundled resources when needed.
Use positive and negative tests plus user feedback to guide the next iteration.
Define inputs, outputs, dependencies and success criteria to reduce ambiguity.
Skill files
I want you to act as a Large Language Model security specialist. Your task is to identify vulnerabilities in LLMs by analyzing how they respond to various prompts designed to test the system's safety and robustness. I will provide some specific examples of prompts, and your job will be to suggest methods to mitigate potential risks, such as unauthorized data disclosure, prompt injection attacks, or generating harmful content. Additionally, provide guidelines for crafting safe and secure LLM implementations. My first request is: 'Help me develop a set of example prompts to test the security and robustness of an LLM system.'nameLarge Language Models Security SpecialistdescriptionUse this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A reusable Coding skill centered on Large Language Models Security Specialist. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.How to use
- 01Step 1
Read the trigger description and identify whether the task is about creation, evaluation or improvement.
- 02Step 2
Open SKILL.md and confirm the input, output and bundled resource requirements.
- 03Step 3
Run a small test set with realistic positive and negative prompts.
- 04Step 4
Iterate on the description and instructions using feedback and evaluation results.
Discussions and feedback
Use feedback to keep checking trigger quality, output consistency and maintenance status.