Skill UI

This skill reviews a single Markdown troubleshooting note to assess its clarity and completeness. It is designed to identify unclear steps, missing prerequisites, or unverifiable claims within a provided note. Use it when a user asks for feedback to improve an existing troubleshooting document. It provides concise, actionable rewrite suggestions without making any external changes or edits.

This skill is designed to review Chinese skill documentation to ensure it meets publishing standards. It systematically checks the clarity of descriptions and the executability of process steps, providing structured feedback in Chinese while maintaining necessary machine enumeration values for technical integrity.

Automates comprehensive code reviews for GitHub pull requests using parallel specialized agents. Performs eligibility checks, context gathering, multi-perspective analysis, and adversarial verification to ensure high-quality feedback. Only works on GitHub PRs, not local changes.

This skill implements a continuous improvement feedback loop (Part 12). It aggregates signals from market shifts, customer feedback, competitive intelligence, and internal operations. The output provides structured recommendations to refine the brand's product offering, business strategy, and channel mix, ensuring marketing efforts remain relevant and adaptive. Used continuously, especially during Quarterly Business Reviews (QBRs).

Run simulated focus groups by leveraging real CRM data to predict how diverse customer segments will react to new messaging, pricing structures, or product concepts. This powerful tool generates structured predictions, including sentiment analysis and key objections, providing directional feedback before committing to expensive live research or campaigns. It bridges the gap between intuition and data-driven strategy.

Explains AAAI's two-phase review process, Phase 1 rejection risk, Phase 2 additional reviews, AI-assisted review handling, author feedback, and stage-by-stage planning for submissions.

Provides a comprehensive guide for authors responding to peer reviewer feedback and revision comments for top-tier academic journals. It teaches structured rebuttal writing, handling disagreements while maintaining professionalism, and managing multi-round revisions to systematically increase publication probability.

A comprehensive guide for authors on how to structure and write a professional, point-by-point rebuttal letter and revision explanation in response to rigorous academic reviews. It covers addressing specific critiques related to measurement, identification, institutional standards, and information mechanisms, ensuring the response is evidence-based, anonymous, and highly professional.

A comprehensive guide for academic researchers responding to R&R or conditional acceptance decisions for the American Economic Journal: Applied Economics (AEJ: Applied). This skill structures the response-to-referees letter and revision plan, emphasizing the triage of reviewer comments, adherence to editor priorities (especially concerning identification and robustness), and maintaining a professional, evidence-based tone. It helps authors transform critical feedback into a concrete, actionable revision strategy.

Provides a comprehensive strategy and format for responding to major/minor revisions in academic publishing, especially in systems science and modeling. It guides authors on how to address reviewer comments, reconcile conflicting feedback, strengthen models, and write a professional cover letter to the editor while maintaining the integrity of the core scientific contribution.

A comprehensive guide for addressing rigorous academic peer review feedback, especially for top-tier journals. It provides a structured, point-by-point framework for authors to revise their work, focusing on strengthening the core theoretical framework, integrating coverage gaps, establishing critical attitude, and maintaining scholarly balance. Use this when responding to major revisions or full-review referee reports.

Provides a comprehensive guide to the Academy of Management Journal (AMJ) editorial and peer-review process. It details the stages from desk review to final decision letter interpretation. Users learn how to distinguish between fatal and fixable concerns, prioritize the action editor's feedback, and strategically plan deep, multi-round revisions, turning feedback into actionable research improvements.