Skill UI

A comprehensive guide and expert skill for mastering Atlassian Jira. Covers project setup, advanced JQL querying, workflow design, issue tracking, automation rules, reporting, and dashboard creation. Essential for technical configuration and operational optimization of Jira instances.

Ports an existing Semgrep rule into each requested language by running applicability analysis, test-first creation, AST-informed rule translation, and validation so that every target-language variant has its own rule+test directory.

This skill provides a structured workflow for porting existing Semgrep security rules to multiple target languages. It guides users through applicability analysis, test-first rule creation, and validation for each language variant, ensuring consistent and accurate security coverage across polyglot codebases.

Monitors Windows process creation events to flag Living Off The Land Binary abuse by matching Event ID 4688/Sysmon 1 logs against LOLBAS database entries, supporting threat hunting and SIEM rule creation for fileless attacks.

This guide details how to integrate Static Application Security Testing (SAST) tools like CodeQL and Semgrep into your CI/CD pipelines using GitHub Actions. It covers setting up automated vulnerability detection on pull requests, tuning rules to minimize false positives, uploading SARIF results for centralized security reporting, and enforcing quality gates to prevent vulnerable code from merging into protected branches. Essential for DevSecOps and compliance (SOC 2, PCI DSS).

This skill maps observed adversary behaviors, security alerts, and detection rules to the MITRE ATT&CK framework. It is essential for quantifying detection coverage, building ATT&CK heatmaps, tagging SIEM alerts, and prioritizing security controls based on known threat actor playbooks. Use it for comprehensive gap analysis and risk reporting.

This guide provides comprehensive strategies to optimize financial workflows within the Fondo system. Key areas covered include accelerating the month-end close process through auto-categorization rule setup, streamlining vendor communications with CPAs via batch processing, and implementing efficient data export caching mechanisms. It is designed to help finance teams achieve faster, more accurate, and highly automated financial reporting.

Provides comprehensive style guidance for writing and refining scientific manuscripts for Acta Automatica Sinica (AAS). This guide covers the structure of the reporting abstract (Purpose/Method/Result/Conclusion), handling bilingual requirements, formatting rules for equations, figures, and adherence to national standards for units and citations (GB/T 7714). Ideal for papers in control theory, robotics, and intelligent systems.

A comprehensive final preflight guide for submitting manuscripts to the American Journal of Political Science (AJPS) via Editorial Manager. It covers strict requirements for double-blind review, including anonymization rules, word count limits, formatting (APSA/Chicago), Supporting Information caps, and human subjects documentation, ensuring the manuscript is ready before hitting submit.

This guide helps authors strategically position their research within active academic debates, particularly in accounting. It ensures the contribution advances a live accounting conversation, clearly distinguishes the work from related finance or economics papers, and adheres to necessary disclosure rules regarding the authors' own concurrent publications. It transforms a manuscript from merely reporting findings into actively joining and advancing a scholarly dialogue.

This guide provides detailed rules for structuring long-form academic papers submitted to the Chinese Journal of Computers (CJC). It teaches authors how to strategically divide content into the main text, appendices, and supplementary materials. The core principle emphasizes that all decision-making evidence required for acceptance must reside in the main manuscript, while supporting details, full proofs, and extra tables belong in supplementary sections.

A detailed guide for authors submitting theoretical machine learning papers (like COLT) regarding the appropriate inclusion and design of numerical simulations. It emphasizes that numerics should only visualize proved bounds, phase transitions, or separations, maintaining the focus on theoretical proofs rather than empirical data. Provides rules for plotting, reporting variability, and maintaining academic honesty.