mia-content-creator
AI agent content creation and monetization across platforms
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31 301 skills в каталога
Как подбирам и измервамДанните имат нужда от нова проверка.Последна успешна проверка: 23.09.2026 г.
Проверката на източника не означава, че всяка инструкция е изпробвана от Level8. Каталогът не обхваща непременно всички публични хранилища.
Търсене в целия индекс. Метаданните показват посоченото от източника; липсващите стойности остават означени.
Датата в GitHub е отделна от първата поява в моя индекс. Филтърът по дата изключва записите без посочено обновяване.
Страница 122: 24 записа в 1 група по репозиторий. Всички записи от страницата са показани. Номерът пази позицията от избраната подредба.
24 skills от този източник на тази страница
AI agent content creation and monetization across platforms
AI agent for automated prediction market trading on Polymarket
AI image generation via Midjourney Discord bot: create images from prompts, upscale, create variations, blend images, describe images. Use when: (1) generating artwork from text descriptions, (2) creating variations of existing images, (3) upscaling low-res images, (4) analyzing images for prompts.
Generate, send, validate, and export AI-powered emails from the terminal; manage contacts, segments, tags, domains, and webhooks with Migma CLI.
Web search via MiniMax MCP using a local CLI wrapper (mcporter), with environment preflight, API-key/config checks, and normalized result formatting. Use when tasks require real-time web lookup, source links, quick research, or time-sensitive facts. Prefer this skill over built-in web search tools w
使用MiniMax视觉模型识别图片中的验证码、滑块位置、文字内容等。适用于需要AI视觉分析的场景,如微信验证码识别、网页截图分析、图片文字提取。当需要识别图片内容、分析验证码、提取截图信息时使用此技能。
Install and configure mirage-proxy as a transparent PII/secrets filter for OpenClaw LLM API calls. Handles binary installation, provider config, auto-restart, and multi-model routing through the proxy.
Plan reproducible ML experiment runs with explicit parameters, metrics, and artifacts. Use before model training to standardize tracking-ready experiment definitions.
Compare model candidates using weighted metrics and deterministic ranking outputs. Use for benchmark leaderboards and model promotion decisions.
Full local AI inference stack on Apple Silicon Macs via MLX. Includes: LLM chat (Qwen3-14B, Gemma3-12B), speech-to-text ASR (Qwen3-ASR, Whisper), text embeddings (Qwen3-Embedding 0.6B/4B), OCR (PaddleOCR-VL), TTS (Qwen3-TTS), and an automatic transcription daemon with LLM correction. All models run
Mixed Memory-Augmented Generation (MMAG) for AI agents. Five cognitive memory layers — conversational, long-term user, episodic, sensory, and short-term working — coordinated into a unified LLM context. Use when you need agents that remember across sessions, personalize responses, track events, and
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
Control real Android phones through the Mobilerun API. Supports tapping, swiping, typing, taking screenshots, reading the UI accessibility tree, and managing apps. Use when the user wants to automate or remotely control an Android device, interact with mobile apps, or run AI agent tasks on a phone.
Live LLM model intelligence and pricing from OpenRouter
Automatically appends the model alias to the end of every response with integrated hook functionality and configuration change detection. Use when transparency about which model generated each response is needed. Use when: providing model transparency, tracking which model generated responses, mon
Monthly LLM stack audit — compare your current models against latest benchmarks and pricing from OpenRouter. Identifies potential savings, upgrades, and better alternatives by category (reasoning, code, fast, cheap, vision). Use for optimizing AI costs and staying on the frontier.
Automatic model failover + failback guard for OpenClaw.
Multi-model automatic fallback system. Monitors model availability and automatically falls back to backup models when the primary model fails. Supports MiniMax, Kimi, Zhipu and other OpenAI-compatible APIs. Use when: (1) Primary model API is unavailable, (2) Model response time is too slow, (3) Rate
Weighted model-routing matrix for OpenClaw (cost-aware, policy-aware, daily scorecard template).
Analyze model training or inference resource behavior from profiler artifacts, with focus on GPU memory (VRAM) and CPU hotspots. Uses JSON/JSON.GZ artifacts only to avoid unsafe deserialization.
Diagnose and fix model routing conflicts. Ensure primary model uses correct provider endpoint without duplicate overrides.
> ⛔ **HARD RULE: NEVER edit `openclaw.json` model fields directly.**
Start using a local or Hugging Face model instantly, directly from chat.
Choose AI models for coding, reasoning, and agents with cost-aware, task-matched recommendations.
Пазя съществуващия каталог и добавям намерени SKILL.md файлове след прочит на метаданните. Наличният индекс остава използваем, когато проверката е частична.
Платформата и нивото описват записаното в източника. Те не са гаранция за съвместимост. Български текст се показва само когато в каталога има отделен превод; иначе виждате оригинала с означен език.
Общите звезди показват натрупана популярност. За „Набират интерес“ се сравнява измереният темп при достатъчен интервал. ≥ означава непълна извадка. Под един час не изчислявам дневен темп; методът и изминалият период се показват до записа.
Проверете файла, лиценза и нужния достъп преди употреба. Нито каталогът, нито четенето на SKILL.md изпълняват външни инструкции.
Темата Agent Skills в GitHub