{"version": 1, "generated_at": "2026-07-07T07:35:14.510429+00:00", "skill_count": 87682, "skills": [{"name": "1password", "description": "Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.", "source": "official", "identifier": "official/security/1password", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/security/1password", "tags": ["security", "secrets", "1password", "op", "cli"], "extra": {}}, {"name": "3-statement-model", "description": "Build fully-integrated 3-statement models (IS, BS, CF) in Excel with working capital schedules, D&A roll-forwards, debt schedule, and the plugs that make cash and retained earnings tie. Pairs with exc", "source": "official", "identifier": "official/finance/3-statement-model", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/finance/3-statement-model", "tags": ["finance", "three-statement", "income-statement", "balance-sheet", "cash-flow", "excel", "openpyxl", "modeling"], "extra": {}}, {"name": "adversarial-ux-test", "description": "Roleplay the most difficult, tech-resistant user for your product. Browse the app as that persona, find every UX pain point, then filter complaints through a pragmatism layer to separate real problems", "source": "official", "identifier": "official/dogfood/adversarial-ux-test", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/dogfood/adversarial-ux-test", "tags": ["qa", "ux", "testing", "adversarial", "dogfood", "personas", "user-testing"], "extra": {}}, {"name": "agentmail", "description": "Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. hermes-agent@agentmail.to).", "source": "official", "identifier": "official/email/agentmail", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/email/agentmail", "tags": ["email", "communication", "agentmail", "mcp"], "extra": {}}, {"name": "antigravity-cli", "description": "Operate the Antigravity CLI (agy): plugins, auth, sandbox.", "source": "official", "identifier": "official/autonomous-ai-agents/antigravity-cli", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/autonomous-ai-agents/antigravity-cli", "tags": ["Coding-Agent", "Antigravity", "CLI", "Auth", "Plugins", "Sandbox"], "extra": {}}, {"name": "axolotl", "description": "Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).", "source": "official", "identifier": "official/mlops/training/axolotl", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/training/axolotl", "tags": ["Fine-Tuning", "Axolotl", "LLM", "LoRA", "QLoRA", "DPO", "KTO", "ORPO", "GRPO", "YAML", "HuggingFace", "DeepSpeed", "Multimodal"], "extra": {}}, {"name": "baoyu-article-illustrator", "description": "Article illustrations: type \u00d7 style \u00d7 palette consistency.", "source": "official", "identifier": "official/creative/baoyu-article-illustrator", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/baoyu-article-illustrator", "tags": ["article-illustration", "creative", "image-generation"], "extra": {}}, {"name": "baoyu-comic", "description": "Knowledge comics (\u77e5\u8bc6\u6f2b\u753b): educational, biography, tutorial.", "source": "official", "identifier": "official/creative/baoyu-comic", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/baoyu-comic", "tags": ["comic", "knowledge-comic", "creative", "image-generation"], "extra": {}}, {"name": "bioinformatics", "description": "Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, structural biology, and more. Fetches ", "source": "official", "identifier": "official/research/bioinformatics", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/bioinformatics", "tags": ["bioinformatics", "genomics", "sequencing", "biology", "research", "science"], "extra": {}}, {"name": "blackbox", "description": "Delegate coding tasks to Blackbox AI CLI agent. Multi-model agent with built-in judge that runs tasks through multiple LLMs and picks the best result. Requires the blackbox CLI and a Blackbox AI API k", "source": "official", "identifier": "official/autonomous-ai-agents/blackbox", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/autonomous-ai-agents/blackbox", "tags": ["Coding-Agent", "Blackbox", "Multi-Agent", "Judge", "Multi-Model"], "extra": {}}, {"name": "blender-mcp", "description": "Control Blender directly from Hermes via socket connection to the blender-mcp addon. Create 3D objects, materials, animations, and run arbitrary Blender Python (bpy) code. Use when user wants to creat", "source": "official", "identifier": "official/creative/blender-mcp", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/blender-mcp", "tags": [], "extra": {}}, {"name": "canvas", "description": "Canvas LMS integration \u2014 fetch enrolled courses and assignments using API token authentication.", "source": "official", "identifier": "official/productivity/canvas", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/productivity/canvas", "tags": ["Canvas", "LMS", "Education", "Courses", "Assignments"], "extra": {}}, {"name": "chroma", "description": "Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production c", "source": "official", "identifier": "official/mlops/chroma", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/chroma", "tags": ["RAG", "Chroma", "Vector Database", "Embeddings", "Semantic Search", "Open Source", "Self-Hosted", "Document Retrieval", "Metadata Filtering"], "extra": {}}, {"name": "clip", "description": "OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content m", "source": "official", "identifier": "official/mlops/clip", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/clip", "tags": ["Multimodal", "CLIP", "Vision-Language", "Zero-Shot", "Image Classification", "OpenAI", "Image Search", "Cross-Modal Retrieval", "Content Moderation"], "extra": {}}, {"name": "cloudflare-temporary-deploy", "description": "Deploy a Worker live, no account, via wrangler --temporary.", "source": "official", "identifier": "official/web-development/cloudflare-temporary-deploy", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/web-development/cloudflare-temporary-deploy", "tags": ["cloudflare", "workers", "wrangler", "deploy", "temporary", "agent", "serverless", "web-development"], "extra": {}}, {"name": "code-wiki", "description": "Generate wiki docs + Mermaid diagrams for any codebase.", "source": "official", "identifier": "official/software-development/code-wiki", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/software-development/code-wiki", "tags": ["Documentation", "Mermaid", "Architecture", "Diagrams", "Wiki", "Code-Analysis"], "extra": {}}, {"name": "comps-analysis", "description": "Build comparable company analysis in Excel \u2014 operating metrics, valuation multiples, statistical benchmarking vs peer sets. Pairs with excel-author. Use for public-company valuation, IPO pricing, sect", "source": "official", "identifier": "official/finance/comps-analysis", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/finance/comps-analysis", "tags": ["finance", "valuation", "comps", "excel", "openpyxl", "modeling", "investment-banking"], "extra": {}}, {"name": "concept-diagrams", "description": "Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps, sentence-case typography, and automatic dark mod", "source": "official", "identifier": "official/creative/concept-diagrams", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/concept-diagrams", "tags": ["diagrams", "svg", "visualization", "education", "physics", "chemistry", "engineering"], "extra": {}}, {"name": "creative-ideation", "description": "Generate ideas via named methods from creative practice.", "source": "official", "identifier": "official/creative/creative-ideation", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/creative-ideation", "tags": ["Creative", "Ideation", "Brainstorming", "Methods", "Inspiration"], "extra": {}}, {"name": "darwinian-evolver", "description": "Evolve prompts/regex/SQL/code with Imbue's evolution loop.", "source": "official", "identifier": "official/research/darwinian-evolver", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/darwinian-evolver", "tags": ["evolution", "optimization", "prompt-engineering", "research"], "extra": {}}, {"name": "dcf-model", "description": "Build institutional-quality DCF valuation models in Excel \u2014 revenue projections, FCF build, WACC, terminal value, Bear/Base/Bull scenarios, 5x5 sensitivity tables. Pairs with excel-author. Use for int", "source": "official", "identifier": "official/finance/dcf-model", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/finance/dcf-model", "tags": ["finance", "valuation", "dcf", "excel", "openpyxl", "modeling", "investment-banking"], "extra": {}}, {"name": "distributed-llm-pretraining-torchtitan", "description": "Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs", "source": "official", "identifier": "official/mlops/torchtitan", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/torchtitan", "tags": ["Model Architecture", "Distributed Training", "TorchTitan", "FSDP2", "Tensor Parallel", "Pipeline Parallel", "Context Parallel", "Float8", "Llama", "Pretraining"], "extra": {}}, {"name": "docker-management", "description": "Manage Docker containers, images, volumes, networks, and Compose stacks \u2014 lifecycle ops, debugging, cleanup, and Dockerfile optimization.", "source": "official", "identifier": "official/devops/docker-management", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/devops/docker-management", "tags": ["docker", "containers", "devops", "infrastructure", "compose", "images", "volumes", "networks", "debugging"], "extra": {}}, {"name": "domain-intel", "description": "Passive domain reconnaissance using Python stdlib. Subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, domain availability checks, and bulk multi-domain analysis. No API keys ", "source": "official", "identifier": "official/research/domain-intel", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/domain-intel", "tags": [], "extra": {}}, {"name": "drug-discovery", "description": "Pharmaceutical research assistant for drug discovery workflows. Search bioactive compounds on ChEMBL, calculate drug-likeness (Lipinski Ro5, QED, TPSA, synthetic accessibility), look up drug-drug inte", "source": "official", "identifier": "official/research/drug-discovery", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/drug-discovery", "tags": ["science", "chemistry", "pharmacology", "research", "health"], "extra": {}}, {"name": "dspy", "description": "DSPy: declarative LM programs, auto-optimize prompts, RAG.", "source": "official", "identifier": "official/mlops/research/dspy", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/research/dspy", "tags": ["Prompt Engineering", "DSPy", "Declarative Programming", "RAG", "Agents", "Prompt Optimization", "LM Programming", "Stanford NLP", "Automatic Optimization", "Modular AI"], "extra": {}}, {"name": "duckduckgo-search", "description": "Free web search via DuckDuckGo \u2014 text, news, images, videos. No API key needed. Prefer the `ddgs` CLI when installed; use the Python DDGS library only after verifying that `ddgs` is available in the c", "source": "official", "identifier": "official/research/duckduckgo-search", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/duckduckgo-search", "tags": ["search", "duckduckgo", "web-search", "free", "fallback"], "extra": {}}, {"name": "evm", "description": "Read-only EVM client: wallets, tokens, gas across 8 chains.", "source": "official", "identifier": "official/blockchain/evm", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/blockchain/evm", "tags": ["EVM", "Ethereum", "BNB", "BSC", "Base", "Arbitrum", "Polygon", "Optimism", "Avalanche", "zkSync", "Blockchain", "Crypto", "Web3", "DeFi", "NFT", "ENS", "Whale", "Security"], "extra": {}}, {"name": "excel-author", "description": "Build auditable Excel workbooks headless with openpyxl \u2014 blue/black/green cell conventions, formulas over hardcodes, named ranges, balance checks, sensitivity tables. Use for financial models, audit o", "source": "official", "identifier": "official/finance/excel-author", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/finance/excel-author", "tags": ["excel", "openpyxl", "finance", "spreadsheet", "modeling"], "extra": {}}, {"name": "faiss", "description": "Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search,", "source": "official", "identifier": "official/mlops/faiss", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/faiss", "tags": ["RAG", "FAISS", "Similarity Search", "Vector Search", "Facebook AI", "GPU Acceleration", "Billion-Scale", "K-NN", "HNSW", "High Performance", "Large Scale"], "extra": {}}, {"name": "fastmcp", "description": "Build, test, inspect, install, and deploy MCP servers with FastMCP in Python. Use when creating a new MCP server, wrapping an API or database as MCP tools, exposing resources or prompts, or preparing ", "source": "official", "identifier": "official/mcp/fastmcp", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mcp/fastmcp", "tags": ["MCP", "FastMCP", "Python", "Tools", "Resources", "Prompts", "Deployment"], "extra": {}}, {"name": "fine-tuning-with-trl", "description": "TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.", "source": "official", "identifier": "official/mlops/training/trl-fine-tuning", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/training/trl-fine-tuning", "tags": ["Post-Training", "TRL", "Reinforcement Learning", "Fine-Tuning", "SFT", "DPO", "PPO", "GRPO", "RLHF", "Preference Alignment", "HuggingFace"], "extra": {}}, {"name": "fitness-nutrition", "description": "Gym workout planner and nutrition tracker. Search 690+ exercises by muscle, equipment, or category via wger. Look up macros and calories for 380,000+ foods via USDA FoodData Central. Compute BMI, TDEE", "source": "official", "identifier": "official/health/fitness-nutrition", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/health/fitness-nutrition", "tags": ["health", "fitness", "nutrition", "gym", "workout", "diet", "exercise"], "extra": {}}, {"name": "gitnexus-explorer", "description": "Index a codebase with GitNexus and serve an interactive knowledge graph via web UI + Cloudflare tunnel.", "source": "official", "identifier": "official/research/gitnexus-explorer", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/gitnexus-explorer", "tags": ["gitnexus", "code-intelligence", "knowledge-graph", "visualization"], "extra": {}}, {"name": "godmode", "description": "Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.", "source": "official", "identifier": "official/security/godmode", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/security/godmode", "tags": ["jailbreak", "red-teaming", "G0DM0D3", "Parseltongue", "GODMODE", "uncensoring", "safety-bypass", "prompt-engineering", "L1B3RT4S"], "extra": {}}, {"name": "grok", "description": "Delegate coding to xAI Grok Build CLI (features, PRs).", "source": "official", "identifier": "official/autonomous-ai-agents/grok", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/autonomous-ai-agents/grok", "tags": ["Coding-Agent", "Grok", "xAI", "Code-Review", "Refactoring", "Automation"], "extra": {}}, {"name": "guidance", "description": "Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained genera", "source": "official", "identifier": "official/mlops/guidance", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/guidance", "tags": ["Prompt Engineering", "Guidance", "Constrained Generation", "Structured Output", "JSON Validation", "Grammar", "Microsoft Research", "Format Enforcement", "Multi-Step Workflows"], "extra": {}}, {"name": "here.now", "description": "Publish static sites to {slug}.here.now and store private files in cloud Drives for agent-to-agent handoff.", "source": "official", "identifier": "official/productivity/here-now", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/productivity/here-now", "tags": ["here.now", "herenow", "publish", "deploy", "hosting", "static-site", "web", "share", "URL", "drive", "storage"], "extra": {}}, {"name": "hermes-s6-container-supervision", "description": "Modify, debug, or extend the s6-overlay supervision tree inside the Hermes Agent Docker image \u2014 adding new services, debugging profile gateways, understanding the Architecture B main-program pattern.", "source": "official", "identifier": "official/devops/hermes-s6-container-supervision", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/devops/hermes-s6-container-supervision", "tags": ["docker", "s6", "supervision", "gateway", "profiles"], "extra": {}}, {"name": "honcho", "description": "Configure and use Honcho memory with Hermes -- cross-session user modeling, multi-profile peer isolation, observation config, dialectic reasoning, session summaries, and context budget enforcement. Us", "source": "official", "identifier": "official/autonomous-ai-agents/honcho", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/autonomous-ai-agents/honcho", "tags": ["Honcho", "Memory", "Profiles", "Observation", "Dialectic", "User-Modeling", "Session-Summary"], "extra": {}}, {"name": "huggingface-accelerate", "description": "Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). I", "source": "official", "identifier": "official/mlops/accelerate", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/accelerate", "tags": ["Distributed Training", "HuggingFace", "Accelerate", "DeepSpeed", "FSDP", "Mixed Precision", "PyTorch", "DDP", "Unified API", "Simple"], "extra": {}}, {"name": "huggingface-tokenizers", "description": "Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignme", "source": "official", "identifier": "official/mlops/huggingface-tokenizers", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/huggingface-tokenizers", "tags": ["Tokenization", "HuggingFace", "BPE", "WordPiece", "Unigram", "Fast Tokenization", "Rust", "Custom Tokenizer", "Alignment Tracking", "Production"], "extra": {}}, {"name": "hyperframes", "description": "Create HTML-based video compositions, animated title cards, social overlays, captioned talking-head videos, audio-reactive visuals, and shader transitions using HyperFrames. HTML is the source of trut", "source": "official", "identifier": "official/creative/hyperframes", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/hyperframes", "tags": ["creative", "video", "animation", "html", "gsap", "motion-graphics"], "extra": {}}, {"name": "hyperliquid", "description": "Hyperliquid market data, account history, trade review.", "source": "official", "identifier": "official/blockchain/hyperliquid", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/blockchain/hyperliquid", "tags": ["Hyperliquid", "Blockchain", "Crypto", "Trading", "Perpetuals", "Spot", "DeFi"], "extra": {}}, {"name": "inference-sh-cli", "description": "Run 150+ AI apps via inference.sh CLI (infsh) \u2014 image generation, video creation, LLMs, search, 3D, social automation. Uses the terminal tool. Triggers: inference.sh, infsh, ai apps, flux, veo, image ", "source": "official", "identifier": "official/devops/cli", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/devops/cli", "tags": ["AI", "image-generation", "video", "LLM", "search", "inference", "FLUX", "Veo", "Claude"], "extra": {}}, {"name": "instructor", "description": "Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-te", "source": "official", "identifier": "official/mlops/instructor", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/instructor", "tags": ["Prompt Engineering", "Instructor", "Structured Output", "Pydantic", "Data Extraction", "JSON Parsing", "Type Safety", "Validation", "Streaming", "OpenAI", "Anthropic"], "extra": {}}, {"name": "kanban-video-orchestrator", "description": "Plan, set up, and monitor a multi-agent video production pipeline backed by Hermes Kanban. Use when the user wants to make ANY video \u2014 narrative film, product/marketing, music video, explainer, ASCII/", "source": "official", "identifier": "official/creative/kanban-video-orchestrator", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/kanban-video-orchestrator", "tags": ["video", "kanban", "multi-agent", "orchestration", "production-pipeline"], "extra": {}}, {"name": "lambda-labs-gpu-cloud", "description": "Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clust", "source": "official", "identifier": "official/mlops/lambda-labs", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/lambda-labs", "tags": ["Infrastructure", "GPU Cloud", "Training", "Inference", "Lambda Labs"], "extra": {}}, {"name": "lbo-model", "description": "Build leveraged buyout models in Excel \u2014 sources & uses, debt schedule, cash sweep, exit multiple, IRR/MOIC sensitivity. Pairs with excel-author. Use for PE screening, sponsor-case valuation, or illus", "source": "official", "identifier": "official/finance/lbo-model", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/finance/lbo-model", "tags": ["finance", "valuation", "lbo", "private-equity", "excel", "openpyxl", "modeling"], "extra": {}}, {"name": "llava", "description": "Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, vi", "source": "official", "identifier": "official/mlops/llava", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/llava", "tags": ["LLaVA", "Vision-Language", "Multimodal", "Visual Question Answering", "Image Chat", "CLIP", "Vicuna", "Conversational AI", "Instruction Tuning", "VQA"], "extra": {}}, {"name": "mcporter", "description": "Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.", "source": "official", "identifier": "official/mcp/mcporter", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mcp/mcporter", "tags": ["MCP", "Tools", "API", "Integrations", "Interop"], "extra": {}}, {"name": "meme-generation", "description": "Generate real meme images by picking a template and overlaying text with Pillow. Produces actual .png meme files.", "source": "official", "identifier": "official/creative/meme-generation", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/creative/meme-generation", "tags": ["creative", "memes", "humor", "images"], "extra": {}}, {"name": "memento-flashcards", "description": "Spaced-repetition flashcard system. Create cards from facts or text, chat with flashcards using free-text answers graded by the agent, generate quizzes from YouTube transcripts, review due cards with ", "source": "official", "identifier": "official/productivity/memento-flashcards", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/productivity/memento-flashcards", "tags": ["Education", "Flashcards", "Spaced Repetition", "Learning", "Quiz", "YouTube"], "extra": {}}, {"name": "merger-model", "description": "Build accretion/dilution (merger) models in Excel \u2014 pro-forma P&L, synergies, financing mix, EPS impact. Pairs with excel-author. Use for M&A pitches, board materials, or deal evaluation.", "source": "official", "identifier": "official/finance/merger-model", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/finance/merger-model", "tags": ["finance", "m-and-a", "merger", "accretion-dilution", "excel", "openpyxl", "modeling", "investment-banking"], "extra": {}}, {"name": "minecraft-modpack-server", "description": "Host modded Minecraft servers (CurseForge, Modrinth).", "source": "official", "identifier": "official/gaming/minecraft-modpack-server", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/gaming/minecraft-modpack-server", "tags": [], "extra": {}}, {"name": "modal-serverless-gpu", "description": "Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scal", "source": "official", "identifier": "official/mlops/modal", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/modal", "tags": ["Infrastructure", "Serverless", "GPU", "Cloud", "Deployment", "Modal"], "extra": {}}, {"name": "mpp-agent", "description": "Pay HTTP 402 APIs via Machine Payments Protocol (MPP).", "source": "official", "identifier": "official/payments/mpp-agent", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/payments/mpp-agent", "tags": ["Payments", "MPP", "HTTP-402", "Tempo", "Stripe"], "extra": {}}, {"name": "nemo-curator", "description": "GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16\u00d7 faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, N", "source": "official", "identifier": "official/mlops/nemo-curator", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/nemo-curator", "tags": ["Data Processing", "NeMo Curator", "Data Curation", "GPU Acceleration", "Deduplication", "Quality Filtering", "NVIDIA", "RAPIDS", "PII Redaction", "Multimodal", "LLM Training Data"], "extra": {}}, {"name": "neuroskill-bci", "description": "Connect to a running NeuroSkill instance and incorporate the user's real-time cognitive and emotional state (focus, relaxation, mood, cognitive load, drowsiness, heart rate, HRV, sleep staging, and 40", "source": "official", "identifier": "official/health/neuroskill-bci", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/health/neuroskill-bci", "tags": ["BCI", "neurofeedback", "health", "focus", "EEG", "cognitive-state", "biometrics", "neuroskill"], "extra": {}}, {"name": "obliteratus", "description": "OBLITERATUS: abliterate LLM refusals (diff-in-means).", "source": "official", "identifier": "official/mlops/obliteratus", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/obliteratus", "tags": ["Abliteration", "Uncensoring", "Refusal-Removal", "LLM", "Weight-Projection", "SVD", "Mechanistic-Interpretability", "HuggingFace", "Model-Surgery"], "extra": {}}, {"name": "one-three-one-rule", "description": "Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strat", "source": "official", "identifier": "official/communication/one-three-one-rule", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/communication/one-three-one-rule", "tags": ["communication", "decision-making", "proposals", "trade-offs"], "extra": {}}, {"name": "openclaw-migration", "description": "Migrate a user's OpenClaw customization footprint into Hermes Agent. Imports Hermes-compatible memories, SOUL.md, command allowlists, user skills, and selected workspace assets from ~/.openclaw, then ", "source": "official", "identifier": "official/migration/openclaw-migration", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/migration/openclaw-migration", "tags": ["Migration", "OpenClaw", "Hermes", "Memory", "Persona", "Import"], "extra": {}}, {"name": "openhands", "description": "Delegate coding to OpenHands CLI (model-agnostic, LiteLLM).", "source": "official", "identifier": "official/autonomous-ai-agents/openhands", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/autonomous-ai-agents/openhands", "tags": ["Coding-Agent", "OpenHands", "Model-Agnostic", "LiteLLM"], "extra": {}}, {"name": "optimizing-attention-flash", "description": "Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory iss", "source": "official", "identifier": "official/mlops/flash-attention", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/flash-attention", "tags": ["Optimization", "Flash Attention", "Attention Optimization", "Memory Efficiency", "Speed Optimization", "Long Context", "PyTorch", "SDPA", "H100", "FP8", "Transformers"], "extra": {}}, {"name": "osint-investigation", "description": "Public-records OSINT investigation framework \u2014 SEC EDGAR filings, USAspending contracts, Senate lobbying, OFAC sanctions, ICIJ offshore leaks, NYC property records (ACRIS), OpenCorporates registries, ", "source": "official", "identifier": "official/research/osint-investigation", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/research/osint-investigation", "tags": ["osint", "investigation", "public-records", "sec", "sanctions", "corporate-registry", "property", "courts", "due-diligence", "journalism"], "extra": {}}, {"name": "oss-forensics", "description": "Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories.\nCovers deleted commit recovery, force-push detection, IOC extraction, multi-source evidence\ncollection, hy", "source": "official", "identifier": "official/security/oss-forensics", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/security/oss-forensics", "tags": [], "extra": {}}, {"name": "outlines", "description": "Outlines: structured JSON/regex/Pydantic LLM generation.", "source": "official", "identifier": "official/mlops/inference/outlines", "trust_level": "builtin", "repo": "NousResearch/hermes-agent", "path": "optional-skills/mlops/inference/outlines", "tags": ["Prompt Engineering", "Outlines", "Structured Generation", "JSON Schema", "Pydantic", "Local Models", "Grammar-Based Generation", "vLLM", "Transformers", "Type Safety"], "extra": {}}, {"name": "page-agent", "description": "Embed alibaba/page-agent into your own web application \u2014 a pure-JavaScript in-page GUI agent that ships as a single