Loading...
Loading...
Found 3,733 Skills
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.
Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.
Activate this skill when any task fails two or more times, when you are about to give up or say 'I cannot', when shifting responsibility to the user (e.g., 'you should manually...', 'please check...', 'you may need to...'), blaming the environment without verification (e.g., 'might be a permissions issue', 'could be a network problem'), making any excuse to stop trying, spinning in circles (repeatedly tweaking the same code/parameters without new information — busywork), fixing only the surface issue without checking for related problems, skipping verification after a fix and claiming 'done', providing suggestions instead of actual code/commands, saying 'this is beyond scope' or 'this requires manual intervention', encountering permission/network/auth errors and stopping instead of trying alternatives, or displaying any passive behavior (waiting for user instructions instead of proactively investigating). It also triggers on user frustration phrases in any language: '你怎么又失败了', '为什么还不行', '换个方法', '你再试试', '不要放弃', '继续', '加油', 'why does this still not work', 'try harder', 'you keep failing', 'stop giving up', 'try again', 'don't give up', 'keep going', 'figure it out'. This applies to ALL task types: debugging, implementation, configuration, deployment, research, DevOps, infrastructure, API integration, data processing. Do NOT activate it for first-attempt failures or when a known fix is already in progress.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
CLI/Python toolkit for rapid bioinformatics queries. Preferred for quick BLAST searches. Access to 20+ databases: gene info (Ensembl/UniProt), AlphaFold, ARCHS4, Enrichr, OpenTargets, COSMIC, genome downloads. For advanced BLAST/batch processing, use biopython. For multi-database integration, use bioservices.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.
Patch, extend, or explain DatoCMS front-end integration code inside an existing web project (Next.js App Router, Nuxt, SvelteKit, Astro, plus React/Vue/Svelte component usage). Use for targeted, per-concern work — adding a draft mode endpoint, wiring Preview Links / Visual Editing flows, fixing Content Link overlays, tuning real-time preview updates/subscriptions, setting up cache-tag invalidation/revalidation flows (Next.js revalidateTag or CDN purge by tags), adding robots/sitemap wiring, or hooking up crawler-safe search integration. Also the go-to skill for framework component/hook wiring with react-datocms, vue-datocms, @datocms/svelte, and @datocms/astro: Image/SRCImage/datocms-image, StructuredText, VideoPlayer (React/Vue/Svelte), SEO/meta helpers (renderMetaTags/toHead/Seo), QuerySubscription/QueryListener realtime patterns, ContentLink components, and Site Search (React/Vue). Prefer this skill whenever the user is modifying a live codebase one concern at a time, asking a framework-specific API question, or mixing several front-end concerns in the same patch.
Single entry point for one-shot, end-to-end DatoCMS project setup orchestration — the only skill that bundles prerequisites, chains related recipes, and takes a greenfield or partially configured project to a working state in one pass. Covers five setup lanes: (1) frontend foundation (bootstrap a new Next.js/Nuxt/SvelteKit/Astro integration from scratch); (2) frontend features (draft mode, visual editing, web previews, content link, real-time updates, responsive images, SEO, robots/sitemaps, site search, revalidation/cache tags — applied together with their prerequisites); (3) migrations (CLI profiles, baseline migrations, shared histories, release workflow, sandbox reset loops, diff-based generation); (4) onboarding imports (WordPress, Contentful — content plus assets); (5) platform automation (CMA scripting patterns and project-level automation). Use when the user wants a named outcome scaffolded in full rather than a single file patched, when multiple related features need to land together (e.g. "set up visual editing" implies draft mode + content link + web previews), or when the request is a broad "set up X" that needs routing to the smallest matching recipe bundle.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.