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docs(website): dedicated page per bundled + optional skill (#14929)

Browse source 
Generates a full dedicated Docusaurus page for every one of the 132 skills
(73 bundled + 59 optional) under website/docs/user-guide/skills/{bundled,optional}/<category>/.
Each page carries the skill's description, metadata (version, author, license,
dependencies, platform gating, tags, related skills cross-linked to their own
pages), and the complete SKILL.md body that Hermes loads at runtime.

Previously the two catalog pages just listed skills with a one-line blurb and
no way to see what the skill actually did — users had to go read the source
repo. Now every skill has a browsable, searchable, cross-linked reference in
the docs.

- website/scripts/generate-skill-docs.py — generator that reads skills/ and
  optional-skills/, writes per-skill pages, regenerates both catalog indexes,
  and rewrites the Skills section of sidebars.ts. Handles MDX escaping
  (outside fenced code blocks: curly braces, unsafe HTML-ish tags) and
  rewrites relative references/*.md links to point at the GitHub source.
- website/docs/reference/skills-catalog.md — regenerated; each row links to
  the new dedicated page.
- website/docs/reference/optional-skills-catalog.md — same.
- website/sidebars.ts — Skills section now has Bundled / Optional subtrees
  with one nested category per skill folder.
- .github/workflows/{docs-site-checks,deploy-site}.yml — run the generator
  before docusaurus build so CI stays in sync with the source SKILL.md files.

Build verified locally with `npx docusaurus build`. Only remaining warnings
are pre-existing broken link/anchor issues in unrelated pages.
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@ -6,7 +6,7 @@ description: "Official optional skills shipped with hermes-agent — install via
# Optional Skills Catalog
Official optional skills ship with the hermes-agent repository under `optional-skills/` but are **not active by default**. Install them explicitly:
Optional skills ship with hermes-agent under `optional-skills/` but are **not active by default**. Install them explicitly:
```bash
hermes skills install official/<category>/<skill>
@ -19,7 +19,7 @@ hermes skills install official/blockchain/solana
hermes skills install official/mlops/flash-attention
```
Once installed, the skill appears in the agent's skill list and can be loaded automatically when relevant tasks are detected.
Each skill below links to a dedicated page with its full definition, setup, and usage.
To uninstall:
@ -27,136 +27,139 @@ To uninstall:
hermes skills uninstall <skill-name>
```
---
## Autonomous AI Agents
## autonomous-ai-agents
| Skill | Description |
|-------|-------------|
| **blackbox** | 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. |
| **honcho** | Configure and use Honcho memory with Hermes — cross-session user modeling, multi-profile peer isolation, observation config, and dialectic reasoning. |
| [**blackbox**](/docs/user-guide/skills/optional/autonomous-ai-agents/autonomous-ai-agents-blackbox) | 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 key. |
| [**honcho**](/docs/user-guide/skills/optional/autonomous-ai-agents/autonomous-ai-agents-honcho) | 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. Use when setting up Honcho, troubleshoo... |
## Blockchain
## blockchain
| Skill | Description |
|-------|-------------|
| **base** | Query Base (Ethereum L2) blockchain data with USD pricing — wallet balances, token info, transaction details, gas analysis, contract inspection, whale detection, and live network stats. No API key required. |
| **solana** | Query Solana blockchain data with USD pricing — wallet balances, token portfolios, transaction details, NFTs, whale detection, and live network stats. No API key required. |
| [**base**](/docs/user-guide/skills/optional/blockchain/blockchain-base) | Query Base (Ethereum L2) blockchain data with USD pricing — wallet balances, token info, transaction details, gas analysis, contract inspection, whale detection, and live network stats. Uses Base RPC + CoinGecko. No API key required. |
| [**solana**](/docs/user-guide/skills/optional/blockchain/blockchain-solana) | Query Solana blockchain data with USD pricing — wallet balances, token portfolios with values, transaction details, NFTs, whale detection, and live network stats. Uses Solana RPC + CoinGecko. No API key required. |
## Communication
## communication
| Skill | Description |
|-------|-------------|
| **one-three-one-rule** | Structured communication framework for proposals and decision-making. |
| [**one-three-one-rule**](/docs/user-guide/skills/optional/communication/communication-one-three-one-rule) | 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 strategies, migration paths), this skill p... |
## Creative
## creative
| Skill | Description |
|-------|-------------|
| **blender-mcp** | 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. |
| **concept-diagrams** | Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language (9 semantic color ramps, automatic dark mode). Best for physics setups, chemistry mechanisms, math curves, physical objects (aircraft, turbines, smartphones), floor plans, cross-sections, lifecycle/process narratives, and hub-spoke system diagrams. Ships with 15 example diagrams. |
| **meme-generation** | Generate real meme images by picking a template and overlaying text with Pillow. Produces actual `.png` meme files. |
| **touchdesigner-mcp** | Control a running TouchDesigner instance via the twozero MCP plugin — create operators, set parameters, wire connections, execute Python, build real-time audio-reactive visuals and GLSL networks. 36 native tools. |
| [**blender-mcp**](/docs/user-guide/skills/optional/creative/creative-blender-mcp) | 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 create or modify anything in Blender. |
| [**concept-diagrams**](/docs/user-guide/skills/optional/creative/creative-concept-diagrams) | 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 mode. Best suited for educational and no... |
| [**meme-generation**](/docs/user-guide/skills/optional/creative/creative-meme-generation) | Generate real meme images by picking a template and overlaying text with Pillow. Produces actual .png meme files. |
| [**touchdesigner-mcp**](/docs/user-guide/skills/optional/creative/creative-touchdesigner-mcp) | Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools. |
## Dogfood
## devops
| Skill | Description |
|-------|-------------|
| **adversarial-ux-test** | Roleplay the most difficult, tech-resistant user for a product — browse in-persona, rant, then filter through a RED/YELLOW/WHITE/GREEN pragmatism layer so only real UX friction becomes tickets. |
| [**inference-sh-cli**](/docs/user-guide/skills/optional/devops/devops-cli) | Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation. Uses the terminal tool. Triggers: inference.sh, infsh, ai apps, flux, veo, image generation, video generation, seedrea... |
| [**docker-management**](/docs/user-guide/skills/optional/devops/devops-docker-management) | Manage Docker containers, images, volumes, networks, and Compose stacks — lifecycle ops, debugging, cleanup, and Dockerfile optimization. |
## DevOps
## dogfood
| Skill | Description |
|-------|-------------|
| **cli** | Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, and social automation. |
| **docker-management** | Manage Docker containers, images, volumes, networks, and Compose stacks — lifecycle ops, debugging, cleanup, and Dockerfile optimization. |
| [**adversarial-ux-test**](/docs/user-guide/skills/optional/dogfood/dogfood-adversarial-ux-test) | 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 from noise. Creates actionable ticke... |
## Email
## email
| Skill | Description |
|-------|-------------|
| **agentmail** | Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses. |
| [**agentmail**](/docs/user-guide/skills/optional/email/email-agentmail) | 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). |
## Health
## health
| Skill | Description |
|-------|-------------|
| **fitness-nutrition** | 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. Computes BMI, TDEE, one-rep max, macro splits, and body fat — pure Python, no pip installs. |
| **neuroskill-bci** | Brain-Computer Interface (BCI) integration for neuroscience research workflows. |
| [**fitness-nutrition**](/docs/user-guide/skills/optional/health/health-fitness-nutrition) | 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, one-rep max, macro splits, and body... |
| [**neuroskill-bci**](/docs/user-guide/skills/optional/health/health-neuroskill-bci) | 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+ derived EXG scores) into responses.... |
## MCP
## mcp
| Skill | Description |
|-------|-------------|
| **fastmcp** | Build, test, inspect, install, and deploy MCP servers with FastMCP in Python. Covers wrapping APIs or databases as MCP tools, exposing resources or prompts, and deployment. |
| **mcporter** | The `mcporter` CLI — list, configure, auth, and call MCP servers/tools directly (HTTP or stdio) from the terminal. Useful for ad-hoc MCP interactions; for always-on tool discovery use the built-in `native-mcp` client instead. |
| [**fastmcp**](/docs/user-guide/skills/optional/mcp/mcp-fastmcp) | 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 a FastMCP server for Claude Code, Cur... |
| [**mcporter**](/docs/user-guide/skills/optional/mcp/mcp-mcporter) | 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. |
## Migration
## migration
| Skill | Description |
|-------|-------------|
| **openclaw-migration** | Migrate a user's OpenClaw customization footprint into Hermes Agent. Imports memories, SOUL.md, command allowlists, user skills, and selected workspace assets. |
| [**openclaw-migration**](/docs/user-guide/skills/optional/migration/migration-openclaw-migration) | 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 reports exactly what could not be mig... |
## MLOps
The largest optional category — covers the full ML pipeline from data curation to production inference.
## mlops
| Skill | Description |
|-------|-------------|
| **accelerate** | Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. |
| **chroma** | Open-source embedding database. Store embeddings and metadata, perform vector and full-text search. Simple 4-function API for RAG and semantic search. |
| **clip** | OpenAI's vision-language model connecting images and text. Zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. |
| **faiss** | 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). |
| **flash-attention** | Optimize transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Supports PyTorch SDPA, flash-attn library, H100 FP8, and sliding window. |
| **guidance** | 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 generation framework. |
| **hermes-atropos-environments** | Build, test, and debug Hermes Agent RL environments for Atropos training. Covers the HermesAgentBaseEnv interface, reward functions, agent loop integration, and evaluation. |
| **huggingface-tokenizers** | Fast Rust-based tokenizers for research and production. Tokenizes 1GB in under 20 seconds. Supports BPE, WordPiece, and Unigram algorithms. |
| **instructor** | Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, and stream partial results. |
| **lambda-labs** | Reserved and on-demand GPU cloud instances for ML training and inference. SSH access, persistent filesystems, and multi-node clusters. |
| **llava** | Large Language and Vision Assistant — visual instruction tuning and image-based conversations combining CLIP vision with LLaMA language models. |
| **modal** | Serverless GPU cloud platform for running ML workloads. On-demand GPU access without infrastructure management, ML model deployment as APIs, or batch jobs with automatic scaling. |
| **nemo-curator** | GPU-accelerated data curation for LLM training. Fuzzy deduplication (16x faster), quality filtering (30+ heuristics), semantic dedup, PII redaction. Scales with RAPIDS. |
| **peft-fine-tuning** | Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Train `<1%` of parameters with minimal accuracy loss for 7B–70B models on limited GPU memory. HuggingFace's official PEFT library. |
| **pinecone** | Managed vector database for production AI. Auto-scaling, hybrid search (dense + sparse), metadata filtering, and low latency (under 100ms p95). |
| **pytorch-fsdp** | Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP — parameter sharding, mixed precision, CPU offloading, FSDP2. |
| **pytorch-lightning** | High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. |
| **qdrant** | High-performance vector similarity search engine. Rust-powered with fast nearest neighbor search, hybrid search with filtering, and scalable vector storage. |
| **saelens** | Train and analyze Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. |
| **simpo** | Simple Preference Optimization — reference-free alternative to DPO with better performance (+6.4 pts on AlpacaEval 2.0). No reference model needed. |
| **slime** | LLM post-training with RL using Megatron+SGLang framework. Custom data generation workflows and tight Megatron-LM integration for RL scaling. |
| **stable-diffusion-image-generation** | State-of-the-art text-to-image generation with Stable Diffusion via HuggingFace Diffusers. Text-to-image, image-to-image translation, inpainting, and custom diffusion pipelines. |
| **tensorrt-llm** | Optimize LLM inference with NVIDIA TensorRT for maximum throughput. 10-100x faster than PyTorch on A100/H100 with quantization (FP8/INT4) and in-flight batching. |
| **torchtitan** | PyTorch-native distributed LLM pretraining with 4D parallelism (FSDP2, TP, PP, CP). Scale from 8 to 512+ GPUs with Float8 and torch.compile. |
| **whisper** | OpenAI's general-purpose speech recognition. 99 languages, transcription, translation to English, and language ID. Six model sizes from tiny (39M) to large (1550M). Best for robust multilingual ASR. |
| [**huggingface-accelerate**](/docs/user-guide/skills/optional/mlops/mlops-accelerate) | 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). Interactive config, single launch comm... |
| [**chroma**](/docs/user-guide/skills/optional/mlops/mlops-chroma) | 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 clusters. Use for semantic search, RAG... |
| [**clip**](/docs/user-guide/skills/optional/mlops/mlops-clip) | 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 moderation, or vision-language tasks w... |
| [**faiss**](/docs/user-guide/skills/optional/mlops/mlops-faiss) | 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, large-scale vector retrieval, or whe... |
| [**optimizing-attention-flash**](/docs/user-guide/skills/optional/mlops/mlops-flash-attention) | 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 issues with attention, or need faster in... |
| [**guidance**](/docs/user-guide/skills/optional/mlops/mlops-guidance) | 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 generation framework |
| [**hermes-atropos-environments**](/docs/user-guide/skills/optional/mlops/mlops-hermes-atropos-environments) | Build, test, and debug Hermes Agent RL environments for Atropos training. Covers the HermesAgentBaseEnv interface, reward functions, agent loop integration, evaluation with tools, wandb logging, and the three CLI modes (serve/process/eva... |
| [**huggingface-tokenizers**](/docs/user-guide/skills/optional/mlops/mlops-huggingface-tokenizers) | Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in &lt;20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integ... |
| [**instructor**](/docs/user-guide/skills/optional/mlops/mlops-instructor) | 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-tested structured output library |
| [**lambda-labs-gpu-cloud**](/docs/user-guide/skills/optional/mlops/mlops-lambda-labs) | 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 clusters for large-scale training. |
| [**llava**](/docs/user-guide/skills/optional/mlops/mlops-llava) | 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, visual question answering, and instruct... |
| [**modal-serverless-gpu**](/docs/user-guide/skills/optional/mlops/mlops-modal) | 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 scaling. |
| [**nemo-curator**](/docs/user-guide/skills/optional/mlops/mlops-nemo-curator) | GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs wit... |
| [**peft-fine-tuning**](/docs/user-guide/skills/optional/mlops/mlops-peft) | Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train &lt;1% of parameters with minimal accuracy loss, or for multi-adapter se... |
| [**pinecone**](/docs/user-guide/skills/optional/mlops/mlops-pinecone) | Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (&lt;100ms p95). Use for production RAG, recommendation systems, or se... |
| [**pytorch-fsdp**](/docs/user-guide/skills/optional/mlops/mlops-pytorch-fsdp) | Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2 |
| [**pytorch-lightning**](/docs/user-guide/skills/optional/mlops/mlops-pytorch-lightning) | High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops w... |
| [**qdrant-vector-search**](/docs/user-guide/skills/optional/mlops/mlops-qdrant) | High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered per... |
| [**sparse-autoencoder-training**](/docs/user-guide/skills/optional/mlops/mlops-saelens) | Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying... |
| [**simpo-training**](/docs/user-guide/skills/optional/mlops/mlops-simpo) | Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpl... |
| [**slime-rl-training**](/docs/user-guide/skills/optional/mlops/mlops-slime) | Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling. |
| [**stable-diffusion-image-generation**](/docs/user-guide/skills/optional/mlops/mlops-stable-diffusion) | State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines. |
| [**tensorrt-llm**](/docs/user-guide/skills/optional/mlops/mlops-tensorrt-llm) | Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantizatio... |
| [**distributed-llm-pretraining-torchtitan**](/docs/user-guide/skills/optional/mlops/mlops-torchtitan) | 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 with Float8, torch.compile, and dist... |
| [**whisper**](/docs/user-guide/skills/optional/mlops/mlops-whisper) | OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast... |
## Productivity
## productivity
| Skill | Description |
|-------|-------------|
| **canvas** | Canvas LMS integration — fetch enrolled courses and assignments using API token authentication. |
| **memento-flashcards** | Spaced repetition flashcard system for learning and knowledge retention. |
| **siyuan** | SiYuan Note API for searching, reading, creating, and managing blocks and documents in a self-hosted knowledge base. |
| **telephony** | Give Hermes phone capabilities — provision a Twilio number, send/receive SMS/MMS, make calls, and place AI-driven outbound calls through Bland.ai or Vapi. |
| [**canvas**](/docs/user-guide/skills/optional/productivity/productivity-canvas) | Canvas LMS integration — fetch enrolled courses and assignments using API token authentication. |
| [**memento-flashcards**](/docs/user-guide/skills/optional/productivity/productivity-memento-flashcards) | 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 adaptive scheduling, and export/impor... |
| [**siyuan**](/docs/user-guide/skills/optional/productivity/productivity-siyuan) | SiYuan Note API for searching, reading, creating, and managing blocks and documents in a self-hosted knowledge base via curl. |
| [**telephony**](/docs/user-guide/skills/optional/productivity/productivity-telephony) | Give Hermes phone capabilities without core tool changes. Provision and persist a Twilio number, send and receive SMS/MMS, make direct calls, and place AI-driven outbound calls through Bland.ai or Vapi. |
## Research
## research
| Skill | Description |
|-------|-------------|
| **bioinformatics** | Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, and structural biology. |
| **domain-intel** | Passive domain reconnaissance using Python stdlib. Subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, and bulk multi-domain analysis. No API keys required. |
| **duckduckgo-search** | Free web search via DuckDuckGo — text, news, images, videos. No API key needed. |
| **gitnexus-explorer** | Index a codebase with GitNexus and serve an interactive knowledge graph via web UI and Cloudflare tunnel. |
| **parallel-cli** | Vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, and monitoring. |
| **qmd** | Search personal knowledge bases, notes, docs, and meeting transcripts locally using qmd — a hybrid retrieval engine with BM25, vector search, and LLM reranking. |
| **scrapling** | Web scraping with Scrapling — HTTP fetching, stealth browser automation, Cloudflare bypass, and spider crawling via CLI and Python. |
| [**bioinformatics**](/docs/user-guide/skills/optional/research/research-bioinformatics) | Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, structural biology, and more. Fetches domain-specific reference material on... |
| [**domain-intel**](/docs/user-guide/skills/optional/research/research-domain-intel) | 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 required. |
| [**drug-discovery**](/docs/user-guide/skills/optional/research/research-drug-discovery) | 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 interactions via OpenFDA, interpret ADMET... |
| [**duckduckgo-search**](/docs/user-guide/skills/optional/research/research-duckduckgo-search) | Free web search via DuckDuckGo — 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 current runtime. |
| [**gitnexus-explorer**](/docs/user-guide/skills/optional/research/research-gitnexus-explorer) | Index a codebase with GitNexus and serve an interactive knowledge graph via web UI + Cloudflare tunnel. |
| [**parallel-cli**](/docs/user-guide/skills/optional/research/research-parallel-cli) | Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive flows. |
| [**qmd**](/docs/user-guide/skills/optional/research/research-qmd) | 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. |
| [**scrapling**](/docs/user-guide/skills/optional/research/research-scrapling) | Web scraping with Scrapling - HTTP fetching, stealth browser automation, Cloudflare bypass, and spider crawling via CLI and Python. |
## Security
## security
| Skill | Description |
|-------|-------------|
| **1password** | Set up and use 1Password CLI (op). Install the CLI, enable desktop app integration, sign in, and read/inject secrets for commands. |
| **oss-forensics** | Open-source software forensics — analyze packages, dependencies, and supply chain risks. |
| **sherlock** | OSINT username search across 400+ social networks. Hunt down social media accounts by username. |
| [**1password**](/docs/user-guide/skills/optional/security/security-1password) | Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands. |
| [**oss-forensics**](/docs/user-guide/skills/optional/security/security-oss-forensics) | Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories. Covers deleted commit recovery, force-push detection, IOC extraction, multi-source evidence collection, hypothesis formation/validation, and st... |
| [**sherlock**](/docs/user-guide/skills/optional/security/security-sherlock) | OSINT username search across 400+ social networks. Hunt down social media accounts by username. |
## web-development
| Skill | Description |
|-------|-------------|
| [**page-agent**](/docs/user-guide/skills/optional/web-development/web-development-page-agent) | Embed alibaba/page-agent into your own web application — a pure-JavaScript in-page GUI agent that ships as a single &lt;script> tag or npm package and lets end-users of your site drive the UI with natural language ("click login, fill userna... |
---
@ -167,4 +170,4 @@ To add a new optional skill to the repository:
1. Create a directory under `optional-skills/<category>/<skill-name>/`
2. Add a `SKILL.md` with standard frontmatter (name, description, version, author)
3. Include any supporting files in `references/`, `templates/`, or `scripts/` subdirectories
4. Submit a pull request — the skill will appear in this catalog once merged
4. Submit a pull request — the skill will appear in this catalog and get its own docs page once merged