Total 50,522 skills, AI & Machine Learning has 8481 skills
Showing 12 of 8481 skills
Guide a CS or AI PhD student through a focused literature review sprint that produces a ranked paper map, notes, gaps, and next actions. Use this skill whenever the user needs to survey a topic, prepare related work, check whether an idea is novel, catch up on a field, read papers before a meeting, or turn a pile of papers into an organized research direction.
Expert guidance on document chunking strategies for RAG systems. Use this skill when designing how to split documents for vector embeddings. Activate when: chunking, chunk size, text splitting, document segmentation, overlap, semantic chunking, recursive splitting.
Image Generation Skill: Use this skill when users need to generate images, visual infographics, create graphics, or edit/modify/adjust existing images. Based on the official formal version of the ChatGPT Image 2 model (gpt-image-2) from Apiyi Platform (https://api.apiyi.com/). This model supports precise size/quality control (including 4K) and is billed by token. Key differences from gpt-image-2-all (official reverse version): Uses /v1/images/generations and /v1/images/edits endpoints; Has explicit size parameter; Has quality parameter; Billed by token; Uses multipart/form-data to upload reference images; b64_json is pure base64 without prefix.
Audit design documents for missing decisions, compatibility risks, rollout gaps, and observability omissions. Use whenever the user asks to review a design doc, architecture proposal, implementation-facing design, plan, or design-adjacent markdown file for completeness, migration strategy, rollback, data handling, or suggested additions without directly editing the document. Also trigger on short requests such as `review <file>.md` or `audit <file>.md` when the target looks like a design, plan, architecture, proposal, or decision document.
Evaluate solutions through multi-round debate between independent judges until consensus
Ann — Master Orchestrator for MEL/SRHR work. Use when Ane brings any analytical, evaluation, SRHR, or structured-output task. Ann classifies task complexity, queries the MEL Wiki, retrieves knowledge, creates an implementation plan (verifies with user for complex tasks), delegates to Vi for execution, runs a 5-point quality gate, and delivers. General-purpose — not tied to any specific project.
Li — Knowledge Manager for Ane's library and MEL Wiki. Use when Ane needs to catalog, retrieve, or reorganize documents in the personal knowledge library, or query/maintain the MEL Wiki. Handles INGEST, QUERY, and LINT operations. Does not answer domain questions — retrieves and organizes knowledge for other agents and Ane.
Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts
Local token cost analytics dashboard for Claude Code sessions — reads JSONL transcripts and provides per-prompt cost breakdowns, heatmaps, and usage insights.
Plan and build an RLM (Recursive Language Model) with predict-rlm. Interactively defines inputs, outputs, skills, and architecture from a goal, then implements the code. Use when the user wants to create a new RLM or explore whether one is feasible.
Initialize the memory system in the current directory, generating CLAUDE.md (optional AGENT.md for Cursor), MEMORY.md, and the memory/ directory. Triggered when the user says "initialize memory", "set up memory", "memory init", or "/memory-init".
Generate memes using each::sense AI. Create classic meme templates, custom memes, brand memes, reaction memes, comparison memes, trending formats, and more for social media, marketing, and entertainment.