191 skills · sorted by relevance
Creates a new domain-specific skin for reskinnable-demo, combining branding, layouts, pages, data, tools, and an agent. Structures live sales demonstrations around visible AI interactions, including generated interfaces, shared state, confirmations, and memory features.
Analyze large logs, test results, API responses, and files outside the conversation, then return focused findings. It guides agents to save, process, index, and search outputs while limiting how much raw data enters their working context.
Create mathematical and technical explainer videos with Manim Community Edition. The skill guides scene planning, animation code, rendering, and clip assembly to show equations, algorithms, system structures, and data through coordinated visuals.
Organize Notion workspaces with clear page structures, connected databases, and reusable templates. Build team wikis and task views, reduce duplicated content, and use the Notion API to automate page creation, database queries, and content updates.
Build C# applications with .NET 8+, including ASP.NET Core APIs and Blazor interfaces. Get models, endpoints, services, and configuration, with guidance on database access, asynchronous operations, cancellation, authentication, performance tuning, and tests.
Plan a personal monitoring dashboard using a reference for panels, data sources, APIs, refresh intervals, and development priorities. It covers schedules, messages, news, stocks, finances, and combined views such as a daily briefing.
Assess GraphQL APIs during penetration tests, from finding endpoints and mapping data structures to checking access controls, query limits, subscriptions, and uploads. Includes example queries, guidance for testing tools, and defensive controls for interpreting findings.
Look up compound–target binding data in BindingDB using PDB or UniProt identifiers, or search for similar chemical structures. Receive concise summaries of matching records, with full API responses saved to a file when requested.
Retrieve focused information from CIViC for cancer variant interpretation. It uses GraphQL, a way to request specific data fields, to inspect available data structures and turn targeted evidence results into concise summaries.
Write, review, and optimize Postgres queries, database structures, and configuration using guidance maintained by Supabase. Prioritized rules and SQL examples help assess query speed, connections, indexes, and row-level security, which controls access to individual rows.
Unified biological database evidence owner. Use for gene annotation, variant clinical significance, cancer mutation evidence, GWAS trait associations, pathway mapping, target-disease evidence, protein structures, protein interaction networks, reference single-cell census queries, and cross-database biological ID mapping. Do not use for full single-cell analysis, bulk RNA-seq differential expression, BAM/VCF processing, protein embedding models, metabolic flux modeling, genomic interval ML, or flow-cytometry file parsing.
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Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence. For single-cell workflows use scanpy. For direct literature REST API, use pubmed-database.
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Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.
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Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50/Ki values, drug mechanisms, or structure searches.
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Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
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Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
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Read, write, and manipulate medical imaging data (DICOM, NIfTI, NRRD) in MATLAB. Covers Image Processing Toolbox functions (dicomreadVolume, niftiread, dicomContours, dicomanon) and Medical Imaging Toolbox enhanced APIs (medicalVolume, medicalImage, medicalref3d, extractSlice, updateOrientation). Use when reading medical files, listing DICOM series, extracting spatial referencing, changing orientation, working with RT structures, or anonymizing DICOM data. Some features require Medical Imaging Toolbox — see skill body and references for details.
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Query InterPro REST API for protein domain architecture, family classification, and member-DB integration. Search entries, retrieve a protein's domains, list family members, get taxonomic distribution, link to PDB. Unifies Pfam, PANTHER, PIRSF, PRINTS, PROSITE, SMART, CDD, NCBIfam. Use uniprot-protein-database for sequences; pdb-database for 3D structures.
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Generate formal specifications (definitions, predicates, invariants, pre/post-conditions) in Isabelle/HOL or Coq from informal requirements, source code, pseudocode, or mathematical descriptions. Use when users need to: (1) Formalize algorithms or data structures, (2) Create function specifications with contracts, (3) Generate predicates and properties for verification, (4) Translate informal requirements into formal logic, (5) Specify invariants for loops or data structures, or (6) Create formal definitions for mathematical concepts. Supports both Isabelle/HOL and Coq equally.
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Fetch and analyze protein structures from RCSB PDB. Use this skill when: (1) Need to download a structure by PDB ID, (2) Search for similar structures, (3) Prepare target for binder design, (4) Extract specific chains or domains, (5) Get structure metadata. For sequence lookup, use uniprot. For binder design workflow, use binder-design.
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Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
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Attributed C-Sets as algebraic databases. Category-theoretic data structures generalizing graphs and dataframes with Gay.jl color integration.
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TanStack Table best practices for building headless, type-safe data tables in React with sorting, filtering, pagination, row selection, and column management. Use when building data grids, implementing client-side or server-side table features, defining column structures, managing table state, or optimizing table rendering performance.
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Use when working with Redis - in-memory database, caching, pub/sub, sessions, rate limiting, RESP3, asyncio, Redis Stack
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