Skill UI

This structured runbook guides users through critical incident response procedures for Instantly.ai. It covers severe issues like account health crises, major campaign failures, deliverability drops, and API outages. The guide provides step-by-step triage, mitigation, and recovery actions (P1-P4) using code examples, ensuring rapid and systematic resolution during platform incidents.

This skill guides users in systematically organizing and documenting a year's worth of past projects into the specific SRED format. It processes scattered evidence—including GitHub PRs, Notion documents, and Linear tickets—to evaluate project suitability, generate comprehensive descriptions, and create structured, standardized reports within Notion. Ideal for formal academic submissions or professional portfolio creation.

This tool systematically structures and derives complex research formulas and theoretical models. It takes scattered equations, messy notes, and ambiguous ideas, transforming them into a coherent, paper-ready derivation package. Use it when you need to build a rigorous theory line, organize explicit assumptions, or clarify the conceptual object underlying a set of formulas.

PIP kicks in when tasks fail repeatedly or the assistant becomes passive, layering Western big-tech performance rhetoric, a systematic debugging methodology, and proactivity enforcement so every code, ops, research, deployment, or writing task is owned, verified, and driven to completion.

Defines a systematic, multi-phase research methodology that prioritizes broad exploration, targeted deep dives, and validation before initiating any content generation, ensuring reliable, multi-angle web intelligence.

This meta-skill acts as a comprehensive Learning Science Coach, teaching users *how* to learn effectively rather than just *what* to study. It draws upon advanced cognitive science principles—including Spaced Repetition, Active Recall, Metacognition, and Bloom's Taxonomy—to diagnose learning gaps, optimize study methods, and build structured, long-term memory retention systems. Ideal for students, professionals, and lifelong learners seeking systematic methods to accelerate knowledge acquisition.

This skill acts as a specialized prompt engineer for AI design tools. It transforms vague, rough UI/UX ideas into polished, highly optimized prompts. It systematically enhances prompts by injecting missing details such as specific components, design system adherence (colors, typography), page structure, and platform context, ensuring the resulting command is professional and ready for superior AI generation.

This skill provides robust methods for handling sensitive data within Notion integrations. It systematically detects Personally Identifiable Information (PII), such as emails, phone numbers, SSNs, and credit cards, within both page properties and rich text content. Users can implement data redaction mechanisms before logging or exporting, ensuring the data handling process fully complies with major privacy regulations like GDPR and CCPA.

This guide details a systematic methodology for identifying specific music tracks. Since searching solely by song title is often too generic, users must first establish constraints on the artist (e.g., nationality, birth year, genre, career type) to narrow the search space. Once the artist is identified, the search should focus on their discography, album tracklists, or specific release years to pinpoint the desired song.

This tool functions as a post-task epilogue, designed to audit and record the entire research journey. It scans the conversation history at the end of a coding or research session to extract critical research artifacts, including decisions, experiments, dead ends, claims, heuristics, and major pivots. It systematically writes this provenance data into the structured `ara/` directory, ensuring a faithful and auditable trace of how the project truly evolved.

This skill addresses vague or ambiguous user requests by initiating a structured, multi-round questioning process. Instead of making assumptions, it systematically clarifies dimensions like audience, scope, tone, and format across several rounds (up to three). This structured approach ensures the resulting output is highly accurate and requires minimal revision cycles.

A powerful 12-agent pipeline designed for academic writers, guiding users through the entire research publication lifecycle. It covers systematic literature review, structural outlining, full drafting, citation compliance, bilingual abstract generation, and simulating peer review. Features include Style Calibration and Writing Quality Checks to ensure high academic rigor and professional polish.