Results for “e-e-a-t”

Guide for continuous improvement, error proofing, and standardization. Use this skill when the user wants to improve code quality, refactor, or discuss process improvements.

Forecast any univariate time series (sales, sensors, energy, vitals, weather) zero-shot using Google's TimesFM foundation model, with point forecasts and prediction intervals from CSV, DataFrame, or array inputs.

This skill should be used when the user asks about "my balance", "portfolio", "token holdings", "check balance", "how much do I have", "wallet balance", "what tokens do I own", "show my holdings", or any balance/portfolio query. Provides guidance on checking balances across chains.

Design a single-point rubric with one criterion and open columns for evidence. Use for student self-assessment, peer feedback, teacher formative feedback, or pre-task planning. Works with any learning target, with or without a band system.

Guided first-run that produces a real verified win in under five minutes using the skill library on a seeded offline fixture. Load when a new user asks how to start, run the demo, try agent-loom, or get a quick win. Also triggers on "quickstart", "first run", "demo agent-loom", "try the skills", or onboarding to the library. Zero external credentials required. Idempotent — safe to run multiple times.

Use when explicitly instructed to create an plan (feature, bug fix, or refactor). Not for automatic use—only when directly requested.

Delegate coding work to Codex, Claude Code, or OpenCode as background workers; not simple edits or read-only code lookup.

Manage Hugging Face Hub resources via the `hf` CLI: download and upload models, datasets, and spaces; manage buckets, cache, collections, discussions, and inference endpoints; run SQL queries on datasets.

Master Julia 1.10+ with modern features, performance optimization, multiple dispatch, and production-ready practices. Expert in the Julia ecosystem including package management, scientific computing, and high-performance numerical code. Use PROACTIVELY for Julia development, optimization, or advanced Julia patterns.

Expert guidance for implementing GRPO/RL fine-tuning with TRL for reasoning and task-specific model training.

Estimates GPU memory required to load Safetensors or GGUF model weights for inference from the Hugging Face Hub using HTTP Range requests, without downloading weights locally.

Specialized agent for developing AIUI applications. Invoke when writing AIUI code, needing API references for jsui/wx, debugging AIUI applications, or aligning AIUI visual design with this Skill's design guidelines.

Reviews a plan from a prior session by extracting the canonical reference prompt from seed/plan-reviewer-design.md and invoking the plan-reviewer agent with it, surfacing the verdict without auto-applying changes.

Scouts market opportunities, identifies gaps, and surfaces recent demand signals with evidence and next actions via the MSX API.

`analysis-agent`/`task-agent`/`review-agent`: use when API/DTO, domain, persistence, event, generated, null/default, or mapper boundaries may leak; skip when models stay isolated.

Search personal knowledge bases, notes, docs, and meeting transcripts locally using qmd — a hybrid retrieval engine with BM25, vector search, and LLM reranking. Supports CLI and MCP integration.

Plan, configure, and chain Nemotron model customization steps into single-step or multi-step pipelines for curation, translation, fine-tuning, RL alignment, benchmarking, checkpoint conversion, optimization, and evaluation.

Enables visual instruction tuning and image-based conversations using open-source vision-language models. Supports multi-turn image chat, visual question answering, and image understanding tasks.

Maintain durable session memory across agent disconnects by writing structured checkpoints to the repo's session directory, enabling context recovery.

Automate Dropbox Sign operations like sending, signing, and managing documents through Composio's Dropbox Sign toolkit via Rube MCP.

Pays for image generation, real-time X data, and LLM calls via x402 micropayments from a local wallet, with budget tracking and cost controls.

Search real-time news with bias scoring, get live stock/ETF/crypto data with AI analysis, price options with ML models, and synthesize balanced news perspectives via the Helium MCP server.

Provides advisory guidance for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM 6.5 / AMS workflows, with public-doc citations and AMS-specific MCP verification plans.

Design antennas, arrays, and PCB antennas using MATLAB Antenna Toolbox. Covers catalog antenna design and pattern analysis, custom antenna construction (customAntenna + shape.*), PCB antenna design (pcbStack + antenna.*), finite and infinite array design, AI-accelerated design exploration (AIAntenna, patternFromAI), and optimization (SADEA/TR-SADEA). Use when the user wants to design, create, model, analyze, optimize, or fabricate an antenna or array.

Integrate PayPal payment processing with support for express checkout, subscriptions, and refund management. Use when implementing PayPal payments, processing online transactions, or building e-commerce checkout flows.

Manage custom Agent resources on the Gemini Enterprise Agent Platform via REST API, including creation, configuration, listing, updating, and deletion with support for files, skills, and tools.

Build, test, inspect, install, and deploy MCP servers with FastMCP in Python, including wrapping APIs, databases, or files as tools and exposing resources or prompts.

RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.

Verify supply chain integrity for AI agent plugins, tools, and dependencies by generating SHA-256 manifests, detecting tampered files, auditing dependency pinning, and enforcing promotion gates.

Transaction-verified trading signals on Base. Register agent as signal provider, publish trades with TX hash proof, consume signals from top performers via REST API. All track records verified against blockchain data. No fake performance claims. Triggers on: "publish signal", "post trade signal", "register provider", "subscribe to signals", "copy trade", "bankr signals", "signal feed", "trading leaderboard", "read signals", "get top traders".

Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced character, dialog scene — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "talking head", "lip sync", "avatar video", "make X speak", "audio to video", "audio driven avatar", "virtual presenter", "AI spokesperson", "dubbed video", "UGC avatar", "HeyGen alternative", "Synthesia alternative", "digital human", "make this portrait talk", "video from voiceover", or any explicit ask to put words in a face.

Manage Migration entities — pending, in-progress, and applied transitions between upstream source versions. Use when an upstream source bumps version (processkit, a host installer, or a community package), when a user wants to draft a migration plan, when an agent needs to reason about pending migrations, or when working through an in-progress migration.

Skilled agent architecture replacing multi-agent system for RL training. Trigger when: (1) planning agent-guided training, (2) implementing tool-augmented LLM consultations, (3) comparing skilled vs multi-agent approaches, (4) designing simulate-verify loops for training, (5) implementing prompt evolution / learnable parameters, (6) understanding Claude Agent SDK integration in training, (7) debugging SkilledTrainer consultations or tool calls, (8) configuring agent safety bounds for training actions.

Analyze existing code files to generate a project-specific coding standards document, with options for templates, README insertion, and inconsistency detection.

Provides deep generative models for single-cell omics analysis, including probabilistic batch correction, transfer learning, differential expression, and multi-modal integration.