Skill UI

Create publication-ready matplotlib figures for academic papers, slides, and reports. Covers bars, trends, scatter, heatmaps, multi-panel layouts, with house style, print/vector export conventions, and parity with figures4papers demos.

A two-layer skill combining disciplined coding practices with terse prose output. The THINK layer enforces surgical edits, simplicity, and goal-driven execution before writing code. The SPEAK layer compresses responses into 'caveman' style for token efficiency, removing filler words while preserving technical accuracy. Ideal for requests requiring brevity, token efficiency, or rigorous engineering discipline.

Execute a comprehensive Test-Driven Development (TDD) workflow enforcing the red-green-refactor discipline. This skill guides test-first development through coordinated agent orchestration, covering requirements analysis, unit test creation, implementation, refactoring, and integration testing with strict coverage thresholds.

This skill serves as a trading journal integrated with Notion, capturing the decision process rather than just trade fills. It records thesis, plan, and emotions at entry, then reviews decision quality against the original plan instead of P&L. It manages trade logs, confirms details, and grades execution to improve trading discipline.

This skill assists in designing user flows and navigation structures based on proven UX patterns. It covers information architecture, navigation patterns like hub and spoke, and screen flow rules. It outputs ASCII flow diagrams, screen inventories, and edge cases. Suitable for planning mobile app and web interface structures before implementing specific pages or copy.

WGM is a robust, agentic methodology designed to transform vague or rough requirements into working, validated software. It enforces a disciplined workflow across six stages: deep alignment (Grill), structured planning, deterministic iterative building (Loop), mandatory holdout-scenario judging, and final documentation audits. It ensures that the resulting code converges against rigorously tested acceptance criteria rather than relying on single-pass generation.

This skill enforces rigorous governance and discipline when AI modifies systems, debugs code, or makes root-cause claims. It mandates safety gates (e.g., backup, blast radius check), demands evidence for every diagnosis, and prevents common AI shortcuts like guessing or deflecting. Use this for critical code modifications, complex debugging, and high-stakes deployments to ensure thoroughness and safety.

Search PubMed biomedical literature via NCBI E-utilities: build MeSH and field-tag queries, filter by publication type and date, retrieve PMIDs, abstracts, and citations for systematic reviews and literature monitoring.

Workflow for searching USPTO patent and trademark records using PatentSearch API, TSDR, file wrapper, and assignment data. Build reproducible IP research logs and compare with secondary sources. Not legal advice.

Use gget CLI or Python package for fast bioinformatics searches across genomic reference databases, including gene metadata, sequences, BLAST/BLAT, enrichment, and reproducible evidence logging.

A systematic workflow for conducting literature reviews across academic, biomedical, technical, and scientific topics. Includes search planning, source screening, synthesis, citation verification, and evidence logging.

A structured rubric-based skill for evaluating academic or scientific work, including research papers, proposals, literature reviews, and methodology sections. It assesses evidence quality, citation support, and provides actionable feedback for revisions.