Skill UI

A comprehensive runbook detailing incident response procedures for failures within the Juicebox AI platform. It guides technical users through diagnosing and resolving critical issues such as API outages, data corruption, quota exhaustion, and export failures, ensuring minimal downtime for recruiting and talent intelligence workflows.

A comprehensive guide for safely migrating monolithic or aging codebases. It details incremental modernization strategies, dependency mapping, and the implementation of the Strangler Fig pattern. Learn how to build safety nets using characterization tests, manage rollouts with feature flags, and achieve zero-downtime refactoring to reduce technical debt without business disruption.

A rigorous, multi-phase auditing skill designed for blockchain protocols. It verifies whether the implemented smart contract code strictly adheres to the detailed specifications provided in whitepapers, design documents, or technical specifications. It performs exhaustive, line-by-line semantic analysis to identify gaps, inconsistencies, and deviations across logic, invariants, and security guarantees, making it essential for formal compliance checking in decentralized systems.

This skill covers the technical process of setting up SSL/TLS inspection (decryption) on next-generation firewalls and proxies. It details how to act as a trusted Man-in-the-Middle to intercept, decrypt, and inspect encrypted HTTPS traffic for malicious payloads, data exfiltration, and policy violations. The workflow includes generating internal Certificate Authority (CA) certificates and deploying them across various operating systems (Windows, macOS, Linux) to ensure visibility into the web's encrypted blind spot.

This script generates a comprehensive diagnostic bundle for CAST AI deployed on a Kubernetes cluster. It automatically collects crucial data including component logs, pod statuses, Helm releases, node inventories, and cluster events into a single archive. Use this tool when preparing a detailed support ticket or performing deep technical troubleshooting.

A comprehensive guide for generating highly detailed and structured embodiment descriptions for patent specifications. It outlines the necessary workflow for describing how an invention is made and used (method, system, apparatus), ensuring the patent meets enablement requirements while strictly differentiating technical descriptions from empirical experimental results.

This comprehensive runbook provides detailed procedures for diagnosing and resolving critical incidents within the Glean enterprise search platform. It covers all severity levels (P1-P4) and failure modes, including API outages, connector synchronization failures, indexing backlogs, and permission drift. It includes diagnostic steps, advanced troubleshooting playbooks, and communication templates for technical support and engineering teams.

A comprehensive guide for drafting and revising top-tier systems papers, specifically for conferences like EuroSys. It details the required academic structure, including building the problem-to-mechanism arc, managing the 12-page technical budget, writing rigorous evaluation sections (including measuring failure cases), and maintaining the necessary double-blind academic voice.

A comprehensive guide for authors submitting to major signal processing conferences like ICASSP. It details how to audit, define, and precisely position a paper's novelty by comparing it against specific literature lanes (SPS journals, conferences, and ML venues). Learn to articulate the technical delta against the nearest work in a constrained, four-page format.

This comprehensive guide provides best practices for packaging supplemental materials and artifacts for top-tier academic conferences like ICDE. It instructs authors on how to build a robust, reproducible evidence chain, including parameterized workload generators, configuration scripts, and detailed logs. The goal is to ensure that reviewers can quickly and accurately validate all performance claims and technical contributions, making the work 'turnkey' and verifiable.

This guide details how to prepare the mandatory video attachment for robotics conference submissions. It covers strict technical specifications (e.g., 180 seconds, 20 MB), the crucial self-containment rule, effective storyboarding techniques, and necessary steps for anonymization. Learn to transform your video from a mere demonstration into robust, undeniable scientific evidence.

Provides comprehensive guidelines for achieving high reproducibility in Machine Learning Systems (MLSys) performance claims. It details how to rigorously control sources of non-determinism (e.g., thermal noise, random seeds) and pin the entire technical stack—from hardware and drivers to frameworks and serving policies—to ensure results can be validated by third parties.