339 skills · sorted by relevance
Study a reference adaptation connecting the shared skillopt_sleep cycle to a custom DeepSeek backend for OpenClaw. It provides prototype wrappers, sample tasks, and a porting checklist for developers building an integration.
Build charts with TradingView's lightweight-charts, including candlesticks, lines, live updates, scales, and annotations. Guidance checks installed types and v5 APIs to support chart integration, framework lifecycle handling, and troubleshooting of common data and display issues.
Manage code changes across multiple AI agents while recording operations and their outcomes. Use previous task histories to find similar attempts, inspect successful patterns, and obtain suggested steps for implementation, code review, deployment, or merging changes.
Automate video editing in JianYing Pro with Python, from importing media and adding narration or subtitles to creating drafts, recording screens, applying zoom effects, and exporting projects, with export options varying by operating system.
Add or update Pallas/Mosaic kernels, specialized computation routines for JAX. The skill covers reference implementations, output and gradient checks, public wrappers, fallback behavior, performance benchmarks, and hardware-specific tuning when requested.
Use this skill when adding NeMo Relay typed wrappers, domain types, or provider codecs while preserving JSON middleware semantics and caller-visible behavior.
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Build Earth2Studio wrappers for transformations at a single time point, from calculating wind speed to using pretrained or diffusion models. The workflow covers input and output coordinates, model loading, tests, and supporting documentation.
Integrate a machine learning weather model into Earth2Studio for forecasts that advance through time. The skill guides wrapper implementation, coordinate handling, model loading, tests, dependency declarations, and documentation updates using a reference inference script.
Build Holoscan SDK 5.x from a selected tag, commit, or development branch using its run wrapper. Check prerequisites, choose build options, preserve existing changes, and verify the result with example tests for SDK development or Early Access features.
Production-ready patterns for Apify SDK and apify-client in TypeScript. Use when building Actors with Crawlee, managing datasets/KV stores, or implementing robust client wrappers with retry and validation. Trigger with "apify SDK patterns", "apify best practices", "apify client wrapper", "crawlee patterns", "idiomatic apify".
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Use this skill for WeChat Mini Program AI via wx.cloud.extend.AI (小程序, wx.cloud apps). Covers generateText and streamText with callbacks (onText, onEvent, onFinish); streamText needs a data wrapper, generateText returns the raw response. Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp (小程序成长计划), cloudbase (main managed), or custom-*; model id goes in the data wrapper `model` field. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (use ai-model-nodejs).
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Position an AI product when everyone claims AI and skeptics call it "just a wrapper." Find the real wedge (data, workflow, trust, domain), make reliability the differentiator, answer "won't the big labs just build this," and stop leading with "AI-powered." Use when your AI or dev tool blends into a sea of similar demos, buyers doubt the accuracy, or you can't say why you win when the model is a commodity.
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Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when "AI wrapper, GPT product, AI tool, wrap AI, AI SaaS, Claude API product, " mentioned.
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Especialista em construir produtos que envolvem APIs de IA (OpenAI, Anthropic, etc.) em ferramentas focadas pela qual as pessoas pagarão. Não apenas 'ChatGPT mas diferente' - produtos que resolvem problemas específicos com IA. Cobre engenharia de prompts para produtos, gestão de custos, rate limiting e construção de negócios de IA defensáveis. Use quando: wrapper de IA, produto GPT, ferramenta IA, envolver IA, IA SaaS.
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Diagnose and safely document Hermes cron script interpreter mismatches, especially when shell scripts are executed as Python or Python wrappers are executed as shell.
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You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.
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Evolutionary file renaming with wrapper files. Enables renames without hard breaks — references are organically updated through usage.
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Renombrado evolutivo de archivos con archivos wrapper. Permite renombrar sin rupturas drásticas — las referencias se actualizan orgánicamente mediante el uso.
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Evolutionary file renaming with wrapper files, plus the terse MOVED-stub standard for whole folder/file moves. Enables renames without hard breaks — references are organically updated through usage.
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Wraps every action item in the JetFormBuilder action editor with custom UI via the 'jet.fb.action.item' wp.hooks filter — the wrapper renders on top of (or alongside) the original action editor for each action and can read/write that action's settings and events array. Use to add quick toggles or panels to every action without modifying each action's own editor — e.g. a TRUE/FALSE/Always button group that drives which custom event the action responds to, a "run once per session" toggle, an inline label override, any visual shortcut over the action's persisted state. Triggers on mentions of "jet.fb.action.item", "useLoopedAction", "useActionsEdit", "useActions", "ActionItemWrapper", "ActionItemBody", "decorate every action", "per-action toggle", or "visual control over action events".
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Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.
The English summary is being prepared. Showing the original description.
You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.
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Work on the Android app — the thin WebView wrapper in `android/`. Use this whenever a task touches the Kotlin sources, the Gradle build, the WebView shell, the native settings screen, LMS server auto-discovery, the JS↔native bridge, app strings/i18n, or the Android CI/lint. Covers the "shell only, UI lives on the web" principle, the debug/release signing split, the static versioning F-Droid needs, and the min/target SDKs, so changes fit the wrapper.
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You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.
The English summary is being prepared. Showing the original description.