AI & ML

Audits ECC Tools GitHub App for cost issues like runaway PR creation, quota bypass, premium-model leakage, and duplicate jobs, using an evidence-first workflow.

Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.

Scans legacy codebases to extract implicit coding conventions across architecture dimensions, resolves conflicts interactively, and generates an enforceable style rules file.

Provides an adaptive methodology for adding machine learning models to existing codebases, covering problem framing, data readiness, architectural decoupling, and baseline model integration.

Rates an agent's own output on five axes — accuracy, completeness, clarity, actionability, conciseness — producing a structured scorecard with evidence and improvement suggestions.

Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.

Design task-local harnesses, eval gates, and reusable skill extraction for adaptive agent workflows.

Fetch any X/Twitter post as clean LLM-friendly JSON, converting x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics.

Design, simulate, and run quantum circuits on quantum computers and simulators using Google's Cirq framework.

Keeps AI coding agents tightly scoped to only change what the user explicitly requested, using the simplest viable solution and asking before expanding scope.

Convert human-written CLAUDE.md files into a structured label format that AI models follow more reliably using fewer tokens.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines with observability and security.

Build real-time voice and multimodal AI applications using Pipecat and Daily, covering pipeline architecture, AI service integration, and transport options.

Designs and orchestrates multi-agent AI teams using the CrewAI framework, covering agent roles, task decomposition, crew processes, memory, and flows.

Generates images using Google Gemini's image generation model for UI placeholders, documentation, and design assets.

Automates job search, auto-apply, resume generation, application tracking, salary intelligence, and recruiter outreach via the JobGPT MCP server.

Build, optimize, and execute quantum circuits using Qiskit on simulators or real quantum hardware from IBM, IonQ, and Amazon Braket.

Analyze single-cell RNA-seq data using Scanpy, including quality control, normalization, clustering, marker gene identification, and visualization.

Compact the current conversation into a handoff document for another agent to pick up, including suggested skills and references to existing artifacts.

Provides guidance and code for production AI workflows including RAG pipelines, vector databases, embedding indexing, prompt engineering, cost estimation, semantic caching, and quality evaluation.

Build cross-platform AI chat interfaces with Makepad using MolyKit, including async utilities, chat widgets, and OpenAI-compatible client integration.

Create publication-quality statistical graphics from tabular datasets with minimal code, supporting multivariate analysis, statistical estimation, and complex multi-panel figures.

Ingest, index, search, and edit video and audio from files, URLs, live streams, or desktop sessions with timestamps, subtitles, overlays, and real-time alerts.

Provides expertise in Langfuse for LLM observability, including tracing, prompt management, evaluation, and integration with LangChain, LlamaIndex, and OpenAI.

Create, manipulate, and analyze complex networks and graphs using the NetworkX Python package.

Search, query, inspect, create, and import data into Weaviate vector database collections using official scripts and references.

Creates and maintains minimal, high-signal AGENTS.md files for AI coding agents, enforcing research-backed best practices for concise agent documentation.

Provides Python tools for biological computation, including sequence manipulation, file I/O, database access, structural bioinformatics, and phylogenetics.

Generates a step-by-step construction plan from a one-line objective, where each step is self-contained and executable by a fresh agent in a new session.

Runs a structured clarifying interview for new project requests before building, then outputs a fully specified prompt.md for a fresh agent session to execute.

Run Bumblebee supply-chain inventory and exposure scans on macOS/Linux to detect compromised packages, extensions, and MCP host configs.

Convert text to speech and speech to text using fal.ai audio models.

Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.

Build production-grade stateful AI agents using LangGraph, covering graph construction, state management, persistence, and human-in-the-loop patterns.

Guides AI agents to apply advanced mathematical and probabilistic techniques (Bloom filters, HyperLogLog, FFT, etc.) for large-scale data problems where classical algorithms are optimal but math offers better asymptotic bounds.

Injects up to 1 million tokens of external context into AI agent memory, auto-summarizes conversations with tone and intent preservation, and compresses multi-turn history into dense token sequences.