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Found 6,930 Skills
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Build applications with InsForge Backend-as-a-Service. Use when developers need to: (1) Set up backend infrastructure (create tables, storage buckets, deploy functions, configure auth/AI) (2) Integrate InsForge SDK into frontend applications (database CRUD, auth flows, file uploads, AI operations, real-time messaging) (3) Deploy frontend applications to InsForge hosting IMPORTANT: Before any backend work, you MUST have the user's Project URL and API Key. If not provided, ask the user first. Key distinction: Backend configuration uses HTTP API calls to the InsForge project URL. Client integration uses the @insforge/sdk in application code.
Create and manage InsForge projects using the CLI. Handles authentication, project setup, database management, edge functions, storage, deployments, and secrets. For writing application code with the InsForge SDK, use the insforge (SDK) skill instead.
Create research posters using HTML/CSS that can be exported to PDF or PPTX. Use this skill ONLY when the user explicitly requests PowerPoint/PPTX poster format. For standard research posters, use latex-posters instead. This skill provides modern web-based poster design with responsive layouts and easy visual integration.
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.
Implements animated effects, transitions, and motion in a Flutter app. Use when adding visual feedback, shared element transitions, or physics-based animations.
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
Generate a Playwright test based on a scenario using Playwright MCP
MUST USE for ANY git operations. Atomic commits, rebase/squash, history search (blame, bisect, log -S). STRONGLY RECOMMENDED: Use with delegate_task(category='quick', load_skills=['git-master'], ...) to save context. Triggers: 'commit', 'rebase', 'squash', 'who wrote', 'when was X added', 'find the commit that'.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls
Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or — when invoked fresh, e.g. "/readout on how github webhook events are processed" — by sharpening scope with clarifying questions and researching the codebase before documenting. The work runs in a child agent so the main conversation's context stays clean. Use whenever the user invokes /readout, says "write this up", "turn this into a doc/page", "make a readout", or asks for a readable, shareable document capturing findings or explaining how something works.