llm-visibility

Name: llm-visibility
Availability: InStock
Author: InerNoro

Scan code for LLM invocations and generate compliance reports with remediation guidance.

2|1|Updated Dec 10, 2025

Search Tags:#audit #llm #compliance #streaming #code-analysis #visibility #prompt-injection

Ready to run

npx skills add https://github.com/inernoro/prd_agent --skill llm-visibility

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: llm-visibility
Source: https://github.com/inernoro/prd_agent/tree/main/.claude/skills/llm-visibility
Command: npx skills add https://github.com/inernoro/prd_agent --skill llm-visibility

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

LLM interactions are often opaque; this Skill visualizes and audits LLM invocation points in code to ensure compliance with a no-blank-wait policy and produce remediation guidance.

Core Features & Use Cases

Automated LLM invocation scanning: scan all code paths to locate LLM calls
Compliance reporting: generate a structured report detailing violations and suggested fixes
Remediation guidance: provide concrete steps to address issues and prevent blank-wait scenarios

Quick Start

Scan your codebase for every LLM invocation and generate a visual audit report with remediation suggestions.

Frequently Asked Questions about llm-visibility

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I audit my codebase for LLM invocation compliance issues?▼

LLM invocation scanning checks code paths to locate calls and verify adherence to a no-blank-wait policy. It produces a compliance report identifying potential wait-time issues across streaming and non-streaming endpoints.

What is a no-blank-wait policy in LLM interactions?▼

A no-blank-wait policy ensures LLM interactions maintain observable progress and utilize streaming outputs to prevent indefinite waiting. It also enforces safe data handling to mitigate data leakage risks during generation.

How do I detect prompt injection risks in my LLM code?▼

Detect prompt injection risks by scanning code to locate LLM invocations and evaluate them against safe data handling requirements. This identifies potential security vulnerabilities and provides remediation guidance to secure your endpoints.

Can I scan both streaming and non-streaming endpoints for LLM wait-time issues?▼

Yes, you can scan both streaming and non-streaming endpoints for LLM wait-time issues. The scanning process works across backend and frontend code to identify potential wait-time violations and ensure observable progress.

How do I get remediation guidance for LLM data leakage risks?▼

Remediation guidance for LLM data leakage risks is generated by scanning code to locate LLM invocations and flagging non-compliant data handling. This produces a structured report with concrete steps to address the identified vulnerabilities.