Read, search, and create notes in the Obsidian vault.
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Review the instructions the agent will receive before you install.
Location: Set via OBSIDIAN_VAULT_PATH environment variable (e.g. in ~/.hermes/.env).
If unset, defaults to ~/Documents/Obsidian Vault.
Note: Vault paths may contain spaces - always quote them.
VAULT="${OBSIDIAN_VAULT_PATH:-$HOME/Documents/Obsidian Vault}"
cat "$VAULT/Note Name.md"
VAULT="${OBSIDIAN_VAULT_PATH:-$HOME/Documents/Obsidian Vault}"
# All notes
find "$VAULT" -name "*.md" -type f
# In a specific folder
ls "$VAULT/Subfolder/"
VAULT="${OBSIDIAN_VAULT_PATH:-$HOME/Documents/Obsidian Vault}"
# By filename
find "$VAULT" -name "*.md" -iname "*keyword*"
# By content
grep -rli "keyword" "$VAULT" --include="*.md"
VAULT="${OBSIDIAN_VAULT_PATH:-$HOME/Documents/Obsidian Vault}"
cat > "$VAULT/New Note.md" << 'ENDNOTE'
# Title
Content here.
ENDNOTE
VAULT="${OBSIDIAN_VAULT_PATH:-$HOME/Documents/Obsidian Vault}"
echo "
New content here." >> "$VAULT/Existing Note.md"
Obsidian links notes with [[Note Name]] syntax. When creating notes, use these to link related content.
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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