发现优质的 AI Agent 技能

Detects insider wallets and concentration risk for Solana meme tokens using on-chain data from DexScreener and Solana RPC nodes. Works without API keys (using public RPC), but a free Helius API key dramatically improves reliability.

> Source: https://docs.carbium.io/page/skill > Drop this into any AI assistant's context to enable Carbium-aware Solana development.

Use these templates when generating slideshows via the genviral API. Before using any template:

Generate AI images and videos through the Partner API. Same model catalog and credit rules as the Genviral web app.

来自 openclaw/skills 技能

> **TL;DR:** Wraps genviral's Partner API into 50+ bash commands. Core flow: `get-pack` → analyze images (metadata + vision) → `generate` with `pinned_images` → `render` → visual review (hard gate) → `create-post` → log to `workspace/performance/log.json`. Studio AI: `studio-models` → `studio-generate-image` (sync) or `studio-generate-video` → `studio-video-status --poll` (async). Auth via `GENVIRAL_API_KEY`. Config in `defaults.yaml`. Instance data in `workspace/`.

Use these templates when generating slideshows via the genviral API. Before using any template:

Generate AI images and videos through the Partner API. Same model catalog and credit rules as the Genviral web app.

来自 openclaw/skills 技能

> **TL;DR:** Wraps genviral's Partner API into 50+ bash commands. Core flow: `get-pack` → analyze images (metadata + vision) → `generate` with `pinned_images` → `render` → visual review (hard gate) → `create-post` → log to `workspace/performance/log.json`. Studio AI: `studio-models` → `studio-generate-image` (sync) or `studio-generate-video` → `studio-video-status --poll` (async). Auth via `GENVIRAL_API_KEY`. Config in `defaults.yaml`. Instance data in `workspace/`.

来自 openclaw/skills 技能

DeepRead is an AI-native OCR platform that turns documents into high-accuracy data in minutes. Using multi-model consensus, DeepRead achieves 97%+ accuracy and flags only uncertain fields for Human-in-the-Loop (HIL) review—reducing manual work from 100% to 5-10%. Zero prompt engineering required.