Skill UI

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Autoresearch Agent runs an autonomous optimization loop that edits a target file, invokes a provided evaluation command, keeps metric-improving commits, drops failures, and repeats indefinitely so engineers can optimize speed, bundle size, prompts, or other measurable goals overnight.

Guides founders on AI positioning, ICP definition, messaging architecture, and quarterly PMF validation so they can translate technical capabilities into the business outcomes buyer-facing teams care about.

This skill initializes a new autoresearch experiment. It guides the user through defining all necessary parameters, including the domain, target files, evaluation commands, metrics, and optimization direction. It is the essential starting point for automated optimization and performance benchmarking cycles.

This tool assists in defining a structured Security Operations Center (SOC) escalation matrix. It maps incident response procedures based on severity (P1-P4), asset criticality, and business impact. Users can model tiered response paths, set Service Level Agreements (SLAs), and implement context-driven automatic escalation triggers to ensure rapid and consistent handling of cybersecurity incidents.

This framework provides a comprehensive solution for tracking vulnerability aging and measuring remediation performance against defined Service Level Agreements (SLAs). It helps organizations enforce severity-based timelines, calculate key performance indicators (KPIs) like Mean Time to Remediate (MTTR), and automate escalation procedures to ensure continuous compliance and improve overall security posture.

This guide details the process of configuring microsegmentation policies to enforce least-privilege access between workloads. It covers the entire workflow, from application dependency mapping and discovery (Phase 1) to defining label-based, default-deny security zones (Phase 2). It is crucial for preventing lateral movement in highly secure, zero-trust architectures using tools like VMware NSX, Illumio, and Calico.

This guide details the process of implementing Zscaler Private Access (ZPA) to replace legacy VPNs with a modern Zero Trust Network Access (ZTNA) framework. It covers deploying App Connectors, defining application segments, and establishing granular access policies based on user identity, organizational user groups, and detailed device posture checks (e.g., compliance, anti-malware status).

This guide details the comprehensive deployment of Palo Alto Networks Prisma Access for implementing a modern SASE-based Zero Trust Network Access (ZTNA). It covers configuring the cloud infrastructure, deploying ZTNA Connectors, defining granular application policies, enforcing device posture via Host Information Profile (HIP), and utilizing GlobalProtect agents for secure, enterprise-grade remote access.

This skill provides a comprehensive guide to deploying a Software-Defined Perimeter (SDP) using the CSA v2.0 specification. It implements core zero trust principles by establishing a dynamic, identity-centric network boundary. The deployment covers Single Packet Authorization (SPA) and mutual TLS (mTLS) to ensure that resources are invisible and inaccessible until a user is fully authenticated and authorized.

This skill automates the entire iterative process of Design Space Exploration (DSE), primarily for computer architecture and EDA problems. It executes complex programs, analyzes resulting objective metrics, and intelligently tunes input parameters (e.g., cache size, pipeline width, optimization passes). It continues iterating until a predefined objective is met or a timeout is reached, making it ideal for optimizing complex system and hardware configurations.

This skill guides the essential pre-testing phase for red team engagements. It defines the scope, objectives, Rules of Engagement (ROE), and threat models using established frameworks like MITRE ATT&CK. By developing a comprehensive plan, users ensure that offensive security testing is performed safely, legally, and within defined operational boundaries, thereby preventing unintended business disruption.