Skill UI

A comprehensive guide for submitting networking research artifacts for SIGCOMM conferences. It dictates how to package code, downscale topologies, substitute traces, and pin environments so that reviewers can independently verify and reproduce the paper's headline results, establishing verifiable scientific claims.

A comprehensive guide for authors in data systems and related fields on achieving rigorous, verifiable reproducibility for academic papers. It mandates detailing the provenance of every claimed result by pinning five critical layers: code version, configuration parameters, dataset source, workload characteristics, and hardware specifications. Best practices include reporting distributions (e.g., percentiles, variance) and maintaining a detailed 'repro debt ledger' to withstand intense peer review.

A comprehensive guide detailing how to package and present research artifacts—including code, hardware designs, and datasets—for major academic conferences. It outlines best practices for both initial review-time evidence and long-term public reuse, ensuring reproducibility and maximizing the chances of adoption by future builders.

This skill outlines a highly rigorous, receipt-driven workflow for managing defects and implementing code corrections. It guides public collaboration by enforcing strict controls over change authority, ensuring comprehensive lineage tracking, and mandating evidence-based validation. Key steps include CodeGraph impact mapping, black-box testing, and adherence to strict change budgets, ensuring every deployed change is fully traceable and robust.

This skill provides comprehensive management for Opencode's permission system. It allows users to review currently always-allowed commands, suggest safe read-only commands, and configure granular access controls using allow/deny/ask patterns. It is essential for optimizing security, performing system audits, and managing the operational scope of the agent.

Policy and workflow for reviewing AI-generated code before merge or execution. Covers AST-based static checks, dependency advisories, isolated behavior tests, and evidence collection with language-specific coverage limits.