Skill UI

This powerful router analyzes complex document types (scanned, medical, table-heavy, etc.) and determines the optimal conversion pipeline (tools, flags, cleanup) to extract data into various formats like Markdown, JSON, or DOCX. It goes beyond simple text extraction by prioritizing the preservation of document structure, relational data, and high fidelity, ensuring the generated output is accurate for downstream machine processing.

A comprehensive skill for capturing and documenting web application and graphical UI states during the development cycle. It supports full-page captures using Playwright, reliable post-processing cropping with PIL, capturing interactive states (hovers, selections), and even handles non-web desktop applications using mss/ctypes.

This skill automatically enriches research wiki pages that are left as bare scaffolds after initial ingestion. It reads multiple external sources (like arXiv/alphaxiv) and fills in 10 structured `_TODO._` sections (e.g., Problem/Gap, Key Results, Open Questions) with detailed prose summaries. Use this skill to transform incomplete research scaffolds into a comprehensive, structured knowledge base.

This skill conducts a comprehensive audit to identify and prioritize automation opportunities within a user's existing workflow. It guides users through a structured intake (covering roles, repetitive tasks, and pain points) and systematically scans connected tools (like Gmail, Slack, Calendar, and CRMs) to surface actionable, ranked quick wins, minimizing implementation effort and maximizing impact.

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).

A powerful tool for deterministic and reproducible retrieval of evidence from specialized academic and policy corpora. It supports searching arXiv (preprints), PubMed/PMC (biomedical literature), and US policy documents. Users can check corpus freshness, retrieve stable metadata, and fetch full-document Markdown for high-reliability research tasks.

This technical skill is designed to verify the compatibility of the Codex CLI with skills compiled from MDA source. Loading this skill confirms that the CLI loader successfully parses the SKILL.md format, adhering to the agentskills.io v1 envelope subset. It is primarily used for testing build pipelines, metadata integrity, and ensuring robust compatibility between MDA compilation and runtime ingestion.

This demo skill verifies the compatibility of MDA-compiled SKILL.md files within the Claude Code environment. It confirms that the skill's frontmatter, metadata structure, and allowed tools are correctly parsed and honored by the loader, ensuring smooth integration of compiled content into the agent workspace. It is a technical utility for development validation.

A self-hosted, semantic memory service designed for AI agents. It allows agents to save worklogs, decisions, and notes, and recall this knowledge across sessions based on meaning rather than exact keywords. Using pgvector and structured workspaces, it maintains persistent, context-aware knowledge bases, making it ideal for collaborative AI projects.

This skill provides an end-to-end, highly reproducible workflow for bulk RNA-seq differential expression analysis. It orchestrates the entire pipeline, guiding users from raw FASTQ reads through Quality Control (QC), trimming, alignment (STAR/Salmon), quantification, generating a gene-level counts matrix, and finally executing differential expression testing (pydeseq2) and pathway enrichment analysis. It is designed for robust, statistically sound, and fully documented results.

This skill runs the Bumblebee scanner on macOS/Linux to perform read-only inventory and exposure checks. It detects compromised packages, developer tools, and host configurations against known security advisories. It is primarily used for supply-chain incident response and vulnerability assessment, providing developers with a clear picture of local system exposure.

A comprehensive toolkit for structuring prospective clinical study designs. It assists in selecting and classifying primary/secondary endpoints, estimating sample size and power for various designs (means, proportions, survival), and scoring overall study plan feasibility (GO/NO-GO). All outputs are estimates routed to specified human experts (clinicians, biostatisticians, regulatory owners), never presented as final facts or regulatory submissions.