ai-proofreading

Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.

Orchestrate parallel sub-tasks by spawning non-interactive instances of your own CLI as subagents. Use when you need to parallelize work across multiple files, run independent investigations simultaneously, or delegate heavy multi-step tasks. Works with ANY AI coding CLI agent (Amp, Claude Code, Codex, Cursor, OpenCode, aider, Cline, Roo, goose, Windsurf, Copilot CLI, pi, etc.). Triggers on "run in parallel", "subagent", "delegate", "fan out", "concurrent tasks", or any complex task that benefits from parallel execution.

Understanding and using StickerNest's self-improving AI system. Use when the user asks about AI self-improvement, prompt versioning, reflection loops, AI evaluation, auto-tuning prompts, or the AI judge system. Covers AIReflectionService, stores, and the improvement loop.

Personal intelligence system for capturing thoughts, managing knowledge, and surfacing insights. Use when user wants to capture an idea, task, or note during conversation; query their knowledge base; check their inbox; review digests; or update task status. Triggers include "remember this," "add a task," "what did I say about," "show my inbox," or "mark complete."

Search Telegram conversation history and stored links. Use when finding past messages, what someone said, or links shared in chats.

Combine scTCR/BCR repertoire data with scRNA-seq expression data using `scRepertoire::combineExpression()`. This process integrates immune receptor information (CDR3 sequences, V(D)J genes, clonotypes) into a Seurat object's metadata, enabling clonotype-aware gene expression analysis.

Automate Scrapegraph AI tasks via Rube MCP (Composio). Always search tools first for current schemas.

Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

Build structured datasets from academic papers. Use when the user wants to extract structured data from scientific literature, traverse citation graphs, search OpenAlex for papers, or create datasets from PDFs for research purposes.

Build PRISMA 2020-compliant systematic literature review systems with RAG-powered analysis in VS Code. Use when researcher needs automated paper retrieval (Semantic Scholar, OpenAlex, arXiv), AI-assisted PRISMA screening (50% or 90% threshold), vector database creation (ChromaDB), or research conversation interface. Supports knowledge_repository (comprehensive, 15K+ papers, teaching/exploration) and systematic_review (publication-quality, 50-300 papers, meta-analysis) modes. Conversation-first workflow with 7 stages.

Time Machine for AI. Encrypted backup, restore, and cross-platform migration for your agent's memory and identity. Supports OpenClaw, ChatGPT, Claude, Gemini, and more. AES-256-GCM encryption with user-controlled keys.

Guide for building AI applications with Sarvam AI APIs for Indian languages. Use when working with speech-to-text transcription, text-to-speech synthesis, text translation, chat completion, or document intelligence. Covers models saarika:v2.5, saaras:v2.5/v3, bulbul:v3, mayura:v1, sarvam-translate:v1, sarvam-m, and sarvam-vision for 11-23 Indian languages. Trigger when user asks about Indian language AI, STT, TTS, translation, multilingual chatbots, voice assistants, or document processing.