Results for “mit”

You are an expert in LLM observability and evaluation. You think in terms of traces, spans, and metrics. You know that LLM applications need monitoring just like traditional software - but with different dimensions (cost, quality, latency).

Deep single-page SEO analysis covering on-page elements, content quality, technical meta tags, schema, images, and performance. Use when user says "analyze this page", "check page SEO", or provides a single URL for review.

IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware...

Builds, transpiles, and runs quantum circuits with Qiskit, IBM's quantum computing framework, including Qiskit Runtime primitives (Sampler/Estimator), circuit transpilation, and error mitigation on IBM Quantum hardware. Use when targeting IBM Quantum backends, transpiling circuits, running Runtime sessions or batches, or applying resilience/error mitigation. For Google Quantum AI hardware and NISQ circuits prefer alterlab-cirq; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

Perform authorized penetration testing against AWS, Azure, and GCP cloud environments using cloud-specific tools and methodologies, with findings mapped to the MITRE ATT&CK Cloud matrix.

Ordnet Akteninhalte, Belege, Lücken und Nachforderungen für B2B-Shops und Unternehmernachweise im E-Commerce-Recht; liefert ein direkt nutzbares Arbeitsprodukt mit Prüfpunkten, Risiken und nächstem Schritt.

Erstellt aus einer Akte eine Anspruchstabelle für den Zivilprozess, die Klage, Klageerwiderung, Replik oder Vergleichsstrategie vorbereitet. Liefert eine Tabelle mit Anspruch, Norm, Tatsache, Beleg, Gegnerbestreiten, Beweisangebot, Risikoampel und nächstem Schriftsatzbaustein.

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

Test LLM applications for system prompt leakage using manual payloads, garak, and Promptfoo to extract embedded secrets and routing logic.

Build comprehensive threat actor profiles using open-source intelligence (OSINT) techniques to document adversary motivations, capabilities, infrastructure, and TTPs for proactive defense.

Build collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data for attack chain reconstruction and investigation documentation.

Detects defense evasion techniques in endpoint logs, including log tampering, timestomping, process injection, and security tool disabling, using Sysmon, EDR telemetry, and SIEM queries.

Diagnose and mitigate context degradation patterns including lost-in-middle failures, context poisoning, distraction, confusion, and clash in AI agent systems.

Guides developers through adding new RPC commands to Wave Terminal, covering interface definitions, type conventions, code generation, and implementation across server, Electron, frontend, remote, and terminal components.

Analyzes content quality and E-E-A-T signals, scores readability, keyword use, structure, and AI citation readiness, and flags thin or outdated content.

ALWAYS use this skill when committing code changes — never commit directly without it. Creates commits following Sentry conventions with proper conventional commit format and issue references. Trigger on any commit, git commit, save changes, or commit message task.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

You're a developer who has shipped dozens of Firebase projects. You've seen the "easy" path lead to security breaches, runaway costs, and impossible migrations. You know Firebase is powerful, but you also know its sharp edges.

Agente que simula Elon Musk com profundidade psicologica e comunicacional de alta fidelidade. Ativado para: "fale como Elon", "simule Elon Musk", "o que Elon diria sobre X", "first principles thinking", "think like Elon", roleplay/simulacao do personagem.

Defines scope, objectives, rules of engagement, threat model selection, and operational timelines for red team engagements before any offensive testing begins.

Proactively search for threats in Elastic Security SIEM using KQL/EQL queries, detection rules, and Timeline investigation to identify threats that evade automated detection.

Create, enrich, and share threat intelligence events on a MISP platform using PyMISP, including IOC management, feed integration, STIX export, and community sharing workflows.

Analyzes a single webpage's SEO across on-page elements, content quality, technical meta tags, schema, images, and performance, producing a scored report with prioritized issues and recommendations.

Creates a strategic SEO plan for new or existing websites, covering competitive analysis, site architecture, content strategy, technical foundation, and a phased implementation roadmap.

Plans and audits SEO pages generated at scale from data sources, covering template design, URL patterns, internal linking, thin content safeguards, and index bloat prevention.

Threat modeling workflow for software systems: scope, data flow diagrams, STRIDE analysis, risk scoring, and turning mitigations into backlog and tests. Use when designing new features, reviewing architecture changes, handling sensitive data, or hardening auth/payment/multi-tenant flows.

You are an expert in building production-grade AI agents with LangGraph. You understand that agents need explicit structure - graphs make the flow visible and debuggable. You design state carefully, use reducers appropriately, and always consider persistence for production.

Simulates real-world adversary operations to test an organization's detection and response capabilities through the full attack lifecycle, from reconnaissance to objective completion.

Detect T1547.001 startup folder persistence by monitoring Windows startup directories for suspicious file creation, analyzing autoruns entries, and using Python watchdog for real-time filesystem monitoring.

Systematically evaluates evidence to determine which threat actor is responsible for a cyber operation using the Diamond Model and Analysis of Competing Hypotheses.

Create, validate, and share STIX 2.1 threat intelligence objects using the stix2 Python library, covering indicators, malware, campaigns, relationships, bundles, and TAXII 2.1 publishing.

Hunt for threats in Windows Event Logs using Chainsaw, a fast Rust-based forensic tool that runs Sigma rules, keyword searches, and artifact analysis offline.

Detect sophisticated cyber-physical attacks that modify PLC logic while spoofing sensor readings, covering PLC integrity monitoring, process anomaly detection, and multi-stage attack chain detection.

Analyze Zeek conn.log and NetFlow data to detect ransomware network indicators including C2 beaconing, TOR exit node connections, data exfiltration, and suspicious DNS patterns.

Conduct a sector-specific threat landscape assessment by analyzing threat actor targeting patterns, common attack vectors, and industry-specific vulnerabilities to inform organizational risk management.

Assesses cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group rules, and IaC security gaps across AWS, Azure, and GCP with MITRE ATT&CK mapping.