Apply Fireflies.ai security best practices for API keys and webhook verification. Use when securing API keys, verifying webhook signatures, or auditing Fireflies.ai security configuration. Trigger with phrases like "fireflies security", "fireflies secrets", "secure fireflies", "fireflies webhook signature", "fireflies HMAC".

Audit automatically audits AI assistant code plugins for security vulnerabilities, best practices, AI assistant.md compliance, and quality standards when user mentions audit plugin, security review, or best practices check. specific to AI assistant-code-plugins repositor... Use when assessing security or running audits. Trigger with phrases like 'security scan', 'audit', or 'vulnerability'.

Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.

Implement CodeRabbit webhook signature validation and event handling. Use when setting up webhook endpoints, implementing signature verification, or handling CodeRabbit event notifications securely. Trigger with phrases like "coderabbit webhook", "coderabbit events", "coderabbit webhook signature", "handle coderabbit events", "coderabbit notifications".

Implement CodeRabbit PII handling, data retention, and GDPR/CCPA compliance patterns. Use when handling sensitive data, implementing data redaction, configuring retention policies, or ensuring compliance with privacy regulations for CodeRabbit integrations. Trigger with phrases like "coderabbit data", "coderabbit PII", "coderabbit GDPR", "coderabbit data retention", "coderabbit privacy", "coderabbit CCPA".

Analyze cryptocurrency market sentiment using Fear & Greed Index, news analysis, and market momentum. Use when gauging overall market mood, checking if markets are fearful or greedy, or analyzing sentiment for specific coins. Trigger with phrases like "analyze crypto sentiment", "check market mood", "is the market fearful", "sentiment for Bitcoin", or "Fear and Greed index".

Detect significant price movements and unusual volume across crypto markets. Calculates significance scores combining price change, volume ratio, and market cap. Use when tracking market movers, finding gainers/losers, or detecting volume spikes. Trigger with phrases like "scan market movers", "top gainers", "biggest losers", "volume spikes", "what's moving", "find pumps", or "market scan".

Aggregate breaking cryptocurrency news from 50+ sources including CoinDesk, CoinTelegraph, The Block, and Decrypt. Use when needing to monitor crypto market news, track announcements, or find coin-specific updates. Trigger with phrases like "get crypto news", "latest Bitcoin headlines", "DeFi announcements", "scan for breaking news", or "check crypto updates".

Execute extract and use project memories from previous sessions for context-aware assistance. Use when recalling past decisions, checking project conventions, or understanding user preferences. Trigger with phrases like "remember when", "like before", or "what was our decision about".

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

**CRITICAL**: Use for ALL CVE discovery and listing. DO NOT call get_cves directly. Use when: "show critical CVEs", "CVEs on hostname X", "remediatable vulnerabilities", "impact of CVE-X", risk assessment. NOT for remediation (use `/remediation`). System-level: FIRST reply = pagination prompt (Step -1). Parsing: references/01-cve-response-parser.py.

Detect test smells, overmocking, flaky tests, and coverage issues. Analyze test effectiveness, maintainability, and reliability. Use when reviewing tests or improving test quality.

| Nuxt 4 production optimization: hydration, performance, testing with Vitest, deployment to Cloudflare/Vercel/Netlify, and v4 migration. Use when: debugging hydration mismatches, optimizing performance and Core Web Vitals, writing tests with Vitest, deploying to Cloudflare Pages/Workers/Vercel/Netlify, or migrating from Nuxt 3 to Nuxt 4.

Create professional Marp presentation slides with 7 beautiful themes (default, minimal, colorful, dark, gradient, tech, business). Use when users request slide creation, presentations, or Marp documents. Supports custom themes, image layouts, and "make it look good" requests with automatic quality improvements.

Reviews and improves Debug.Log usage in Unity C# projects following structured logging principles: context tags, severity contracts, boundary-based placement, and criticality tiers. Detects common antipatterns (naked Debug.Log, logging in Update, stringly-typed errors), adds missing logs at system/state/error/external boundaries, and scaffolds project-wide logging infrastructure (LogTag constants, formatting helpers, conventions). Use when the user mentions logging, Debug.Log, log messages, debugging, or asks to improve observability in Unity code.

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

Use when the user wants to review Qodo PR feedback or fix code review comments. Capabilities: view issues by severity, apply fixes interactively or in batch, reply to inline comments, post fix summaries (GitHub, GitLab, Bitbucket, Azure DevOps, Gerrit)

Instruments Java, Python, Node.js, .NET, and Go applications with OpenTelemetry SDKs to send traces, metrics, and logs to Coralogix. Use for SDK-side OTel setup, OTLP exporter env vars, Coralogix resource attributes, APM transaction samplers, Kubernetes Operator injection, or debugging missing traces, metrics, logs, or no telemetry from an application. Not for OTel Collector config (use opentelemetry-collector), OTTL authoring (use opentelemetry-ottl), eBPF instrumentation, or Lambda layers.