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找到 5779 個 Skills
Skills 列表
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
gmgn-holder-analysis
Token holder chip analysis — deep analysis of holder structure including chip distribution, entry cost, whale/dev/KOL behavior, risk wallets (rat traders, bundlers, snipers), related wallets, smart money signals, and an AI rating based purely on token structure. Use when user asks about holder analysis, 筹码分析, 持仓分析, chip structure, who is holding, or whether a token is safe to buy based on its holder composition.
gmgnai
new-unity-project
Use when starting a brand-new Unity game or project from scratch — "make/start/create a new game", "bootstrap a Unity project", "I want to build a <genre> game", "scaffold/prototype a game", game jam, greenfield, blank project, project setup. A guided flow that gathers the concept, target platforms, and monetization, installs the Editor in the background while it asks, then creates the project and source control and installs packages — delegating the mechanics to the unity-cli and unity-package-management skills and handing off monetization to the dedicated skills. Does not scaffold gameplay code.
unity-technologiesbuild-live-game
Build and operate a live game using Unity Services. Use when the user needs to implement, connect, or debug backend-driven features — battle passes, achievements, player progression, cloud saves, leaderboards, matchmaking, virtual economies, server-authoritative logic, anti-cheat, player accounts and authentication, remote configuration, feature flags, A/B testing, analytics, or cloud resource deployment. Triggers on live-ops, live service, backend, server authority, cloud code, cloud save, remote config, player data, retention, monetization loop, season pass, ranking, multiplayer sessions, lobbies, or any Unity Services integration.
unity-technologies
social-media-context-sms
When the user wants to set up or update their social media profile, voice, audience, content pillars, or platform preferences. Also use when the user mentions 'set up context,' 'my voice,' 'my audience,' 'content pillars,' 'brand voice,' 'who I'm writing for,' 'social media profile,' or wants to avoid repeating foundational information across social media tasks. Use this at the start of any new project before using other social media skills — it creates .agents/social-media-context-sms.md that all other skills reference.
blacktwistcontent-pattern-analyzer-sms
When the user wants to find patterns in what content works and what doesn't. Also use when the user mentions 'what's working,' 'content patterns,' 'best topics,' 'best format,' 'best time to post,' 'analyze my content,' 'do more of,' 'do less of,' or 'what should I change.' For raw metrics, see performance-analyzer-sms. For audience-specific analysis, see audience-growth-tracker-sms. For actionable recommendations, see optimization-advisor-sms.
blacktwist
csv-data-summarizer
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
coffeefuelbumpanalyze-project
Rigor Analyze / Rigor Audit read-only skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation patterns without modifying code or running heavy jobs. Do not use for active command execution, broad refactoring, speculative code adaptation, or automatic bug fixing.
lllllllamaexplore-code
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, verified contribution claims, or default repository analysis.
lllllllamaai-research-reproduction
Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, score chasing, or broad research assistance outside repository-grounded reproduction.
lllllllamapaper-context-resolver
Rigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
lllllllama