Skill UI

Spreadsheet creation, format conversion (ODS/XLSX/CSV), formulas, data automation with LibreOffice Calc.

Automate Coda documents, tables, formulas, permissions, and publishing via Composio’s Rube MCP pipeline; search tool schemas first, then orchestrate doc browsing, row upserts, exports, and sharing workflows.

Applies empirically grounded cognitive science frameworks to help CS and AI researchers generate genuinely novel directions through bisociation, analogical reasoning, constraint shifts, and problem reformulation workflows.

This skill guides users in transforming chaotic debugging efforts into a structured, systematic process. It provides a methodology for tracking down elusive bugs, investigating complex performance degradation, and resolving critical production incidents. Users learn to capture necessary logs, formulate testable hypotheses, narrow the scope using techniques like binary search, and methodically verify fixes in distributed systems environments.

Provides automated guidance for business automation workflows focused on building, validating, and optimizing Excel formulas, helping teams iterate on spreadsheets, email processing, and workflow optimization quickly.

Identifies and rewrites AI-generated phrasing by removing inflated claims, promotional language, formulaic structures, and robotic cadence so reviewed prose sounds natural, varied, and personality-driven.

Build and tune Obsidian Base files to define database-like views, filters, formulas, and summaries for notes, so you can craft tables, cards, lists, and dashboards inside your vault.

Guidance for creating, editing, and analyzing .xlsx workbooks while preserving formulas, formatting, and assumptions, leveraging pandas/openpyxl for data work and LibreOffice recalc to ensure error-free financial models.

Defines strict guidelines for creating and maintaining Excel financial models, covering zero formula errors, industry color coding, number formatting, documented assumptions, and mandatory use of Excel formulas to ensure accuracy and auditability before recalculation.

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.

PyDESeq2 brings the DESeq2 differential expression workflow to Python, letting users load bulk RNA-seq counts, specify design formulas, fit DESeq2 models, run Wald tests with FDR correction, optionally apply apeGLM shrinkage, and export gene-level statistics within pandas/AnnData pipelines.

Fast-reference component for SaaS finance metrics, providing formulas, benchmarks, and red-flag cues during reviews, meetings, or decision checks without deep explanations.