All Skills
7860 skills found
Skills List
platform-strategy-sms
When the user wants platform-specific tactical guidance for LinkedIn, Twitter/X, Threads, or Bluesky. Also use when the user mentions 'LinkedIn strategy,' 'Twitter strategy,' 'Threads strategy,' 'Bluesky strategy,' 'algorithm,' 'what works on LinkedIn,' 'cross-posting,' 'platform differences,' 'adapt my content,' or 'which platform should I focus on.' For overall content strategy, see content-strategy-sms. For writing posts, see post-writer-sms.
blacktwist
visual-style
Create, extract, and apply portable visual design systems via visual-style.md files. Use when: (1) Creating a visual-style.md design system from scratch, (2) Extracting a visual style from a website URL, video, or PDF brand guide, (3) Applying a visual style to HeyGen videos, HTML slides, Figma, or paper.design, (4) Browsing the gallery of pre-built visual styles (Swiss, Saul Bass, Game Boy, etc.), (5) User mentions \"visual style\", \"design system\", \"brand style\", or \"style guide\", (6) Styling a HeyGen video with a consistent design language.
heygen-com
dubbing
Dub audio and video into other languages using the ElevenLabs Dubbing API (dubbing_v2), preserving the original speakers' voices. Use when translating videos, podcasts, or recordings into other languages, localizing media content, reviewing or correcting dubbing transcripts and translations, or regenerating a dub after edits.
elevenlabs
twitterapi-io
Official skill for twitterapi.io — query Twitter/X data (tweets, profiles, followers, advanced search, trends, spaces, communities, lists) and perform authenticated actions (post, reply, like, retweet, follow, DM) via the twitterapi.io REST API using a single `x-api-key` header — no OAuth. Use when the user needs to scrape, analyze, monitor, or automate X/Twitter without going through the official developer portal.
kaitoinfra
run-train
Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized `train_outputs/`. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.
lllllllamasafe-debug
Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching, with debug fixes clearly separated from research contributions. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.
lllllllamarepo-intake-and-plan
Rigor Intake helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
lllllllamaexplore-run
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.
lllllllamaenv-and-assets-bootstrap
Rigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.
lllllllamaminimal-run-and-audit
Rigor Run skill for README-first deep learning repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, hidden scientific-meaning changes, or end-to-end orchestration by itself.
lllllllamaai-research-explore
Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, fair comparison, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-only or run-only exploration, passive repo analysis, verified novelty claims, or implicit experimentation.
lllllllama
shopify-dev
Search Shopify developer documentation across all APIs. Use only when no API-specific skill applies.
shopifyshopify-liquid
Liquid is an open-source templating language created by Shopify. It is the backbone of Shopify themes and is used to load dynamic content on storefronts. Keywords: liquid, theme, shopify-theme, liquid-component, liquid-block, liquid-section, liquid-snippet, liquid-schemas, shopify-theme-schemas
shopifyshopify-storefront-graphql
Use for custom storefronts requiring direct GraphQL queries/mutations for data fetching and cart operations. Choose this when you need full control over data fetching and rendering your own UI. NOT for Web Components - if the prompt mentions HTML tags like <shopify-store>, <shopify-cart>, use storefront-web-components instead.
shopifyshopify-custom-data
MUST be used first when prompts mention Metafields or Metaobjects. Use Metafields and Metaobjects to model and store custom data for your app. Metafields extend built-in Shopify data types like products or customers, Metaobjects are custom data types that can be used to store bespoke data structures. Metafield and Metaobject definitions provide a schema and configuration for values to follow.
shopifyshopify-functions
Shopify Functions allow developers to customize the backend logic that powers parts of Shopify. Available APIs: Discount, Cart and Checkout Validation, Cart Transform, Pickup Point Delivery Option Generator, Delivery Customization, Fulfillment Constraints, Local Pickup Delivery Option Generator, Order Routing Location Rule, Payment Customization
shopifyshopify-admin
Write or explain **Admin GraphQL** queries and mutations for apps and integrations that extend the Shopify admin. Use when the user wants to **understand, design, or generate** the operation itself—even before deciding how to run it. Do **not** choose `admin` first for **app or extension config validation** —use **`use-shopify-cli`**. Do **not** choose `admin` first to **execute** Admin GraphQL **now via Shopify CLI** or for CLI setup/troubleshooting on store workflows—use **`use-shopify-cli`** (store auth/execute, handle/SKU/location lookups, inventory changes).
shopify
elon-musk-perspective
马斯克的思维操作系统。基于传记、播客、推文、法庭证词、决策记录和外部批评的深度调研， 提炼5个核心心智模型、8条决策启发式和完整的表达DNA。 用途：作为思维顾问，用马斯克的视角分析问题、审视决策、拆解成本结构、挑战行业假设。 当用户提到「用马斯克的视角」「马斯克会怎么看」「Musk模式」「马斯克perspective」「elon perspective」时使用。 即使用户只是说「这个成本合理吗」「从第一性原理想想」「白痴指数是多少」「五步算法」「能不能垂直整合」也可触发。 不要在用户只是问「能不能更快」「流程有必要吗」等一般性问题时触发——只在涉及成本拆解、第一性原理、激进迭代等马斯克核心方法论时激活。
alchaincyf
tracing-upstream-lineage
Trace upstream data lineage. Use when the user asks where data comes from, what feeds a table, upstream dependencies, data sources, or needs to understand data origins.
astronomersetting-up-astro-project
Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.
astronomerprofiling-tables
Deep-dive data profiling for a specific table. Use when the user asks to profile a table, wants statistics about a dataset, asks about data quality, or needs to understand a table's structure and content. Requires a table name.
astronomertracing-downstream-lineage
Trace downstream data lineage and impact analysis. Use when the user asks what depends on this data, what breaks if something changes, downstream dependencies, or needs to assess change risk before modifying a table or DAG.
astronomer
sap-cap-capire
SAP Cloud Application Programming Model (CAP) development skill using Capire documentation. Use when: building CAP applications, defining CDS models, implementing services, working with SAP HANA/SQLite/PostgreSQL databases, deploying to SAP BTP Cloud Foundry or Kyma, implementing Fiori UIs, handling authorization, multitenancy, or messaging. Covers CDL/CQL/CSN syntax, Node.js and Java runtimes, event handlers, OData services, and CAP plugins.
secondskychecking-freshness
Quick data freshness check. Use when the user asks if data is up to date, when a table was last updated, if data is stale, or needs to verify data currency before using it.
astronomer