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Found 2,392 Skills
Use when the user asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.
The precise design and UI vocabulary used on index.how/to/articulate — covering typography, color, iconography, layout, interaction, motion, accessibility, information architecture, copywriting, tools, analysis, and components. Use when reaching for the exact word for a design concept ("what's the term for the space between two specific letters?"), when a UI idea is described loosely and needs its proper name, when choosing between confusable near-synonyms (badge vs tag, tooltip vs popover, opacity vs visibility, kerning vs tracking), or when writing or reviewing copy, specs, or commits and you want exact terminology instead of vague language.
Use when adding, modifying, optimizing, or debugging CuTile autotuning code. Trigger signals: `exhaustive_search` / `replace_hints` / `hints_fn` / `cuda.tile.tune` in code, `autotune` in filenames, or correctness/performance issues in autotuned CuTile kernels. Covers: tune-once/cache/launch pattern, per-architecture configs (sm80–sm120), parameter space design (tile sizes, occupancy, num_ctas), and 7 common pitfalls with solutions.
Brev managed GPU instances with Docker support. Use when running TAO training, evaluation, or inference on Brev GPU instances, managing Brev deployments, or dispatching TAO jobs through the Brev CLI. Trigger phrases include "run on Brev", "Brev GPU instance", "submit job to Brev", "Brev CLI deployment".
Manage workspace knowledge files and libraries in the Cargo content domain — upload, list, rename, move, and remove files (PDFs, CSVs, text), and create or sync native and connector-backed libraries for retrieval-augmented generation (RAG). Use when the user wants to upload or organize knowledge files, build a knowledge library, or sync an external knowledge source. To attach these to an agent, use the cargo-ai skill.
Inspect and edit the workspace's git-backed context repository (the GTM knowledge base of markdown/MDX files) and its runtime sandbox using the Cargo CLI. Use when the user wants to browse/read/write/edit context files, run a command in the sandbox, or inspect the context knowledge graph.
Build MCP servers in Python with FastMCP to expose tools, resources, and prompts to LLMs. Supports storage backends, middleware, OAuth Proxy, OpenAPI integration, and FastMCP Cloud deployment. Prevents 30+ errors. Use when: creating MCP servers, or troubleshooting module-level server, storage, lifespan, middleware, OAuth, background tasks, or FastAPI mount errors.
Search and retrieve content from Twitter/X. Get user info, tweets, replies, followers, communities, spaces, and trends via twitterapi.io.
CRITICAL: Use for generics, traits, zero-cost abstraction. Triggers: E0277, E0308, E0599, generic, trait, impl, dyn, where, monomorphization, static dispatch, dynamic dispatch, impl Trait, trait bound not satisfied, 泛型, 特征, 零成本抽象, 单态化
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Expand seeds and escape convergent ideation. Use when you have the start of an idea and want to grow it, when brainstorming produces the same ideas every time, or when you need to explore possibility space.
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.