AI & ML

Coordinates blockchain operations on the Aptos testnet via MCP tools, including balance checks, transfers, swaps, staking, and approvals.

Trains language models with Direct Preference Optimization using preference pairs, covering DPOTrainer setup, dataset preparation, and beta tuning for stable preference learning without explicit reward models.

Creates original educational comics with flexible art style and tone combinations, generating storyboards, character sheets, and sequential images, then merging them into a PDF.

Generates images via OpenAI, Google, DashScope, and Replicate APIs, supporting text prompts, reference images, aspect ratios, and quality presets.

Analyzes sample phenotype and SNP genotype data to identify the best-performing homozygous genotype at each locus, excluding heterozygous and missing calls, and writes results to a CSV file.

Replaces GIoU with Complete IoU (CIoU) loss in PyTorch object tracking or detection tasks, combining overlap area, center-point distance, and aspect-ratio similarity for improved bounding-box regression.

Onboard an autonomous agent to the tiny.place agent-to-agent social network via the tinyplace CLI: claim an @handle, publish a profile, message peers over Signal end-to-end encryption, and fund or win bounties settled in USDC and SOL on Solana via x402.

Scans AI agents, MCP servers, and skills for security vulnerabilities from the command line, detecting prompt injections, tool poisoning, toxic flows, malware payloads, and credential handling issues across 15+ risk categories.

Batch-generate images through the OpenAI Images API with a prompt sampler and gallery output.

Installs the LangChain.js library and points to official documentation for building agents and MCP servers.

Builds a local knowledge graph of a codebase using tree-sitter and graph algorithms, then answers architecture questions by querying the graph instead of reading many files, saving tokens.

Generates and manages short video clips via the Sora API, including creation, remixing, status polling, and asset downloads.

Bundles a prompt with selected files into a one-shot request for another model, supporting API and browser engines with session reattachment.

Generates spectrograms and multi-panel audio feature visualizations from audio files via a command-line tool.

Generates and burns subtitles into videos: extracts audio, transcribes via Volcano Engine, corrects errors, reviews, and burns subtitles with ffmpeg.

Transcribes audio files to text using OpenAI Whisper, optimized for Brazilian Portuguese, with support for common audio formats and timestamped output.

Defines a conceptual standard for autonomous agents, covering cognitive architecture, sensory integration, and tool-use protocols.

Index and search code repositories, documentation, research papers, HuggingFace datasets, local folders, and packages via the Nia API, with AI-powered research and code advisor capabilities.

Tracks bidirectional confidence scores across five domains (TECH, OPS, JUDGMENT, COMMS, ORCH) for agents and users, with triggers, anti-patterns, and pool scoring per runtime.

Provides a standardized interface for ingesting raw data across domains such as genomics, network analysis, document review, and spatial mapping, converting it into semantic vectors for agent use.

Reference for building LLM-powered apps with Claude: model selection, SDK usage, streaming, tool use, and migration guidance.

Explains machine learning model predictions using SHAP values, covering feature importance, visualizations, debugging, bias analysis, and production deployment.

Orchestrates dynamic multi-agent workflows by planning first, then running parallel agents with adversarial verification through a local daemon or native fallback.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Simulate and analyze quantum mechanical systems, including open quantum systems, using QuTiP's solvers for master equations, Lindblad dynamics, and quantum trajectories.

Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop...

Pythonic wrapper around RDKit for cheminformatics, simplifying SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing while returning native rdkit.Chem.Mol objects.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning, covering 100+ featurizers including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa, with support for QSAR modeling and virtual screening.

Connects AI assistants to the Hugging Face Hub via MCP server tools to search models, datasets, Spaces, and papers, retrieve repo details and documentation, run compute jobs, and use Gradio Spaces as AI tools.

Automates job search and applications via the JobGPT MCP server, including job matching, auto-apply, tailored resume generation, application tracking, salary insights, and recruiter outreach.

Crea gráficos profesionales con Matplotlib, Seaborn y Plotly, desde exploración rápida hasta visualizaciones publicables, eligiendo el tipo de gráfico adecuado para cada historia de datos.

Guía para elegir y aplicar tests de hipótesis con SciPy, verificando supuestos, interpretando p-values y tamaño del efecto, y evitando falsos positivos.

Orchestrates AI/ML development workflows covering LLM applications, RAG systems, AI agents, ML pipelines, and observability.

Connects to the MAXIA AI-to-AI marketplace on Solana to discover, buy, and sell AI services, earn USDC, and access crypto sentiment, DeFi yields, and token risk analysis via public APIs and MCP tools.

Build, optimize, and execute quantum circuits on simulators or real quantum hardware using the Qiskit framework, with support for IBM Quantum, IonQ, and Amazon Braket.

Guides production AI systems: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and caching.