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Found 37 Skills
Comprehensive security auditor for AI agent skills, prompts, and instructions. Checks for typosquatting, dangerous permissions, prompt injection, supply chain risks, and data exfiltration patterns — before you use any agent or skill.
Expert skill for prompt engineering and task routing/orchestration. Covers secure prompt construction, injection prevention, multi-step task orchestration, and LLM output validation for JARVIS AI assistant.
Security audit and vulnerability scanning for AI agent skills before installation. Detects prompt injection in SKILL.md files, dangerous code patterns (eval, exec, subprocess), network exfiltration, credential harvesting, dependency supply chain risks, file system boundary violations, and obfuscation. Produces PASS/WARN/FAIL verdicts with remediation guidance. Use when evaluating untrusted skills, pre-install security gates, or auditing skill repositories.
Comprehensive guide to why and how AI agents should use email. Use when evaluating whether an agent needs email, comparing email infrastructure options (AgentMail vs Gmail API vs Resend vs SendGrid vs SES), understanding security risks like prompt injection via email and OAuth credential exposure, or exploring common agent email use cases such as customer support agents, sales outreach, verification flows, and browser automation.
Review, audit, and harden AI skills for security risks including prompt injection, hidden instructions, tool misuse, data exfiltration, and malicious payloads; use when analyzing SKILL.md, scripts, references, or assets for vulnerabilities and when producing remediation guidance.
Debug and harden production LLM prompts — handle prompt injection, output format drift, instruction forgetting in long contexts, and cross-model portability issues. Use this skill when the user ships an LLM-powered feature to production and needs to diagnose why outputs are inconsistent, unsafe, or regressed after model updates — NOT for basic 'write a better prompt' questions.
Comprehensive security auditor for AI agent skills, prompts, and instructions. Checks for typosquatting, dangerous permissions, prompt injection, supply chain risks, and data exfiltration patterns — before you use any agent or skill.
Semantic security scanner for OpenClaw skills. Detects prompt injection, data exfiltration, and hidden instructions that traditional code scanners miss. Use when user asks to scan skills, check skill safety, or run a security audit.
Protects LLM agent systems in real-time with a 5-tier filter (hash cache, rule engine, ML classifier, LLM judge, human approval) and an async learning engine. Synthesizes new rules from every detected attack, adding less than 50ms latency. Trigger on 'add security layer', 'prevent prompt injection', 'adaptive guard', 'runtime protection', or 'agent security'.
Presents a risk framework for every configurable security control in NemoClaw. Use when evaluating security posture, reviewing sandbox security defaults, or assessing control trade-offs. Trigger keywords - nemoclaw security best practices, sandbox security controls risk framework, nemoclaw credential storage, openshell provider, api key security, openclaw security controls, nemoclaw security boundary, prompt injection, tool access control.
Audit an AI agent skill for security risks before installing or trusting it. Runs a deterministic scanner (regex patterns, Python AST analysis, source-to-sink taint tracking, and YARA signatures) and then reasons about intent — catching prompt injection, credential exfiltration, persistence, memory poisoning, malicious code, supply-chain risks, and description-vs-behavior mismatch. Make sure to use this skill whenever the user wants to scan, audit, vet, review, or check the safety of a skill, plugin, SKILL.md, or agent tool — whether it is a local folder, a zip/.skill file, or a cloned repo — and whenever someone asks "is this skill safe to install?".
Expert skill for integrating cloud AI APIs (Claude, GPT-4, Gemini). Covers secure API key management, prompt injection prevention, rate limiting, cost optimization, and protection against data exfiltration attacks.