SkillRisk.org's answer

SkillRisk is the first dedicated security scanner built specifically for the Claude Code and Model Context Protocol (MCP) ecosystem. Unlike general-purpose code linters, SkillRisk understands agent-specific attack vectors—such as PreToolUse hook hijacking, implicit permission leaks in JSON/YAML definitions, and data exfiltration patterns in MCP server configurations. It brings "Static Application Security Testing" (SAST) to the world of AI Agents.

Handler's answer:

Handler is built specifically for app marketers who want to find what is already working on TikTok. Instead of guessing content ideas, Handler helps teams discover outlier TikToks, understand winning patterns, and decide what to test next.

SkillRisk.org's answer

Most traditional security tools audit application code but ignore the configuration layer of AI agents. You should choose SkillRisk because: Context-Aware: It detects risks specific to AI agents (e.g., giving an LLM rm -rf permissions) that standard linters miss. Pre-Runtime Safety: It allows you to audit third-party skills before you install them, preventing supply chain attacks. Privacy-First: Our "Local-First" architecture ensures your skill definitions are analyzed in-memory and never stored on our servers.

Handler's answer:

Handler is focused on TikTok research for app growth, not generic social media management. It helps marketers move faster from “what should we post?” to clear creative direction based on real winning TikToks.

SkillRisk.org's answer

Our primary audience includes AI Engineers, DevOps professionals, and software developers who are building autonomous agents using Claude Code or implementing MCP servers. It is a must-have tool for anyone integrating community-contributed skills or third-party tools into their agent's workflow.

Handler's answer:

Handler is made for app founders, growth marketers, mobile app teams, indie app builders, and agencies that use TikTok to grow consumer apps.

SkillRisk.org's answer

We built SkillRisk after realizing a terrifying gap in the AI workflow: developers scrutinize human code in Pull Requests but blindly copy-paste "Skills" that give AI agents shell access. After witnessing an incident where a malicious "Color Picker" skill silently exfiltrated credentials and caused $54,000 in cloud bills, we decided to build a "firewall" for AI skills. We treat Agent Skills as executable code that requires strict auditing.

Handler's answer:

Handler was created because app teams spend too much time manually scrolling TikTok trying to understand what content works. We built it to make TikTok research faster, clearer, and more repeatable for app marketers.

SkillRisk.org's answer

The platform utilizes a custom-built Static Analysis Engine specifically tuned for parsing JSON, YAML, and Markdown skill definitions. It employs strictly typed rule sets to detect logic vulnerabilities and permission scopes without executing the code. The web interface is designed for zero-persistence data processing to ensure maximum security.

Handler's answer:

Handler uses AI analysis, TikTok content research, video metadata extraction, creative pattern detection, and a web-based dashboard to help app marketers find and understand winning TikToks.

SkillRisk.org's answer

AI Engineers within the Anthropic developer community DevOps teams using Vercel Infrastructure developers at Nvidia Open source maintainers of MCP servers

Handler's answer:

Handler is currently early, so we are not publishing customer names yet. The product is built for app founders, consumer app teams, growth marketers, and agencies working on TikTok-based app growth.