Skill UI

A comprehensive, scalable Python toolkit designed for end-to-end single-cell RNA-seq data analysis. It supports crucial steps including quality control (QC), normalization, dimensionality reduction (PCA, UMAP, t-SNE), cell clustering, and differential gene expression analysis. The skill provides ready-to-run scripts for analyzing various formats (e.g., .h5ad, 10X, R-native) and generating publication-quality visualizations and cell type annotations.

This skill provides a systematic framework for evaluating the rigor of scientific claims, research methodology, and evidence quality. It guides users through assessing experimental design validity, identifying various types of biases (e.g., selection, cognitive), and applying established grading frameworks like GRADE or Cochrane Risk of Bias. Ideal for systematic reviews, peer review, and critical analysis of scientific literature.

A comprehensive skill for generating visually engaging, scientifically rigorous slide decks for academic talks. It guides users through planning, structuring content, and ensuring design consistency for conferences, thesis defenses, and research seminars. Supports integrating complex figures and citations into professional PDF presentations.

This skill automates the process of transforming high-level product specifications, requirements, and design documents into a detailed, actionable, and executable task plan. It follows a multi-stage workflow, including context loading, parallel research, and two rigorous review gates (Task Plan Review and Task-Graph Sanity Review). The output provides properly sized (1-3 hours), logically sequenced tasks, ensuring every requirement is covered and dependencies are explicitly managed, dramatically improving project planning accuracy.

This skill provides an interactive, comprehensive quality review for technical design documents. It systematically validates a feature's readiness for implementation by assessing critical issues, identifying strengths, and providing a clear GO/NO-GO decision with actionable next steps. Ideal for ensuring architectural soundness and catching risks early in the development lifecycle.

Provides technology-agnostic guidance for architecting and reviewing modular systems. This skill covers core architectural principles such as bounded contexts, state isolation, explicit contracts, and failure containment. Use it when determining service boundaries, assessing coupling between domains, or designing new greenfield architectures without assuming a specific framework, language, or repository structure.

This skill provides actionable strategies and code patterns to significantly reduce Anima API costs. It focuses on optimizing usage through generation caching, detecting component changes for incremental generation, and implementing smart policies to minimize unnecessary API calls. Ideal for managing large-scale design-to-code workflows and controlling API budget.

This skill demonstrates how to create an event-driven pipeline using Figma's Webhooks. It listens for design file changes and automatically triggers Anima to regenerate production-ready code components (e.g., React/TypeScript/Tailwind). Ideal for integrating continuous design updates into CI/CD workflows.

This skill integrates the agent with the Matrix/Element messaging platform. It enables full conversational capabilities, allowing users to receive real-time alerts, search content, and control connected systems (such as cameras) directly from a designated Matrix room. It supports multi-turn interactions, including sending files, reacting, editing, and managing threads.

This skill integrates an AI agent (Clawdbot) with Signal, one of the most private messaging platforms. It enables automated communication by utilizing the signal-cli tool to perform actions such as sending messages, sending files, reacting, and replying within a designated chat channel. Ideal for building secure, automated bot interactions in private messaging environments.

This skill provides robust mechanisms to interact with the Clari API, specifically designed to handle rate limiting (HTTP 429 errors) and manage asynchronous bulk export jobs. It implements exponential backoff and sequential scheduling, ensuring reliable data retrieval and forecasting exports without hitting API limits. Ideal for automated data pipelines and background job processing.

A robust orchestration skill designed for managing large-scale, complex machine learning experiments on remote GPU clusters via SSH. It handles multi-seed sweeps, sequential wave transitions, and deep learning pipelines requiring state management. Features include OOM-aware automatic retries, cleanup of stale terminal sessions, and deterministic scheduling to prevent race conditions, making it ideal for grid computing and staged training.