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Found 51 Skills
Implement AI image generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to create images from text descriptions, generate visual content, create artwork, design assets, or build applications with AI-powered image creation. Supports multiple image sizes and returns base64 encoded images. Also includes CLI tool for quick image generation.
The meta-skill that powers all other AI tools. Prompt engineering for creative applications is the art and science of communicating with AI models to produce exactly what you envision—in images, video, audio, and text. This isn't just "write better prompts." It's understanding how different models interpret language, how to structure requests for different modalities, how to iterate systematically, and how to build prompt libraries that encode your creative vision. The best prompt engineers have developed intuition for what words trigger what responses in each model. This skill is foundational—it amplifies the effectiveness of every other AI creative skill. Master this, and you master the interface to all AI creation. Use when "prompt, prompting, prompt engineering, better prompts, prompt optimization, how to prompt, prompt strategy, prompt library, prompt template, make AI understand, prompt-engineering, prompting, meta-skill, ai-creative, foundational, optimization, iteration" mentioned.
FFmpeg-based 4-step video creation: Validate, Prepare, Encode, Verify. Use when user wants to combine a static image with audio to create an MP4 video, create a music video from cover art, or produce podcast/YouTube video from an image and audio file. Use for "image to video", "static video", "mp4 from image", "album art video", or "audio visualization". Do NOT use for video editing, live streaming, or generating images.
PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
Data validation patterns including schema validation, input sanitization, output encoding, and type coercion. Use when implementing validate, validation, schema, form validation, API validation, JSON Schema, Zod, Pydantic, Joi, Yup, sanitize, sanitization, XSS prevention, injection prevention, escape, encode, whitelist, constraint checking, invariant validation, data pipeline validation, ML feature validation, or custom validators.
Extracts hidden or encoded text from GCODE files by analyzing toolpath geometry and coordinate data. This skill should be used when tasks involve decoding text from 3D printing files, recovering embossed or engraved text from GCODE, or CTF-style challenges involving GCODE analysis. Applies to any task requiring geometric reconstruction of text from CNC or 3D printer movement commands.
Video/audio/image processing with FFmpeg and ImageMagick. Tools: FFmpeg (video/audio), ImageMagick (images). Capabilities: format conversion, encoding (H.264/H.265/VP9/AV1), streaming (HLS/DASH), filters, effects, thumbnails, watermarks, batch processing, hardware acceleration (NVENC/QSV). Actions: convert, encode, resize, crop, compress, extract, merge, stream, transcode media. Keywords: FFmpeg, ImageMagick, video encoding, audio extraction, image resize, thumbnail, watermark, HLS, DASH, H.264, H.265, VP9, AV1, codec, bitrate, framerate, resolution, aspect ratio, filter, overlay, concat, trim, fade, batch processing. Use when: converting video/audio formats, encoding with specific codecs, generating thumbnails, creating streaming manifests, extracting audio from video, batch processing images, adding watermarks, optimizing file sizes.
Render JSON artifacts into readable UI with an inspect-first, facts-first workflow. Use when Codex needs to turn JSON files, JSON-producing shell commands, CLI output artifacts, or unknown structured payloads into a declarative UI spec that can be rendered natively by the harness or through a terminal-native reference renderer, including cases with repeated child records encoded as aligned arrays.
Classical cipher analysis playbook. Use when encountering substitution ciphers, Vigenere, transposition, XOR, or encoded text in CTF challenges that requires frequency analysis, Kasiski examination, or known-plaintext cryptanalysis.
Encode and decode Swift types to and from JSON, property lists, and other external representations using Codable, JSONEncoder, and JSONDecoder. Use when implementing API response parsing, custom CodingKeys for key remapping, custom init(from:) or encode(to:) for complex transformations, nested or flattened JSON structures, heterogeneous array decoding, date and data decoding strategies, lossy array wrappers, Codable integration with URLSession, SwiftData, or UserDefaults, or when configuring encoder/decoder output formatting and key strategies.
Identify undefined areas in the current feature specification by asking up to 5 highly targeted clarification questions, and encode the answers back into the specification. Trigger words include: "speckit-clarify", "speckit clarification", "specification clarification", "feature clarification", "identify ambiguities", "clarify requirements".