Security

Control Apple TV, HomePod, and AirPlay devices via pyatv (scan, stream, playback, volume, navigation).

Community incident reporting for AI agents. Contribute to collective security by reporting threats.

Audit-ready decision artifacts for LLM outputs — assumptions, risks, recommendation, and review gating (schema-valid JSON).

Identify recurring charges and subscriptions from receipts or email exports, and produce a clean summary with renewal dates, price changes, and cancellation drafts. Use when a user wants to audit spending without initiating payments or cancellations.

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

Test skill to demonstrate the audit badge; do not use it for real workflows.

Install and configure the ClawGuard security plugin - an LLM-as-a-Judge guardrail that detects and blocks risky tool calls

Build Rails applications with proper conventions, performance patterns, and security practices.

Verify AI agents, check trust scores (0-100), fetch A2A agent cards, discover marketplace agents, apply guardrails for security and compliance. Use when user mentions agent verification, trust scores, agent discovery, A2A protocol, agent identity, agent marketplace, guardrails, security policies, content moderation, or asks "is this agent safe?" or "find agents that can [task]" or "apply guardrails to protect my agent".

Formats text according to specified style guidelines. A clean example skill with no security issues.

Runs a full CORE-EEAT 80-item content quality audit, scoring content across 8 dimensions with weighted scoring by content type. Produces a detailed report with per-item scores, dimension analysis, and a prioritized action plan.

Avoid common Solidity mistakes — reentrancy, gas traps, storage collisions, and security pitfalls.