Documentation Index Fetch the complete documentation index at: https://docs.egregorelabs.io/llms.txt
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Built-in Scaffolds Egregore includes three production-ready scaffolds for common agent capabilities.
InternalNotesScaffold Automatic note-taking and memory system.
Features
Automatic capture : Remembers user preferences, facts, and instructionsPersistent storage : Notes survive across sessionsSearch and retrieval : Query notes by content or categoryOrganization : Categorize notes by topic
Usage agent = Agent( provider = "openai:gpt-4" , enable_scaffolds = True ) # Agent automatically captures notes agent.call( "My email is alice@example.com" ) agent.call( "I prefer dark mode" ) agent.call( "Remember: I work in Python" ) # Access notes notes_scaffold = agent.scaffolds[ "notes" ] print (notes_scaffold.state.notes) # ["Email: alice@example.com", "Preference: dark mode", "Language: Python"] # Agent recalls automatically agent.call( "What's my email?" ) # "Your email is alice@example.com"
Operations # Add note manually notes_scaffold.add_note( "Important: project deadline March 15" ) # Search notes results = notes_scaffold.search_notes( "email" ) # ["Email: alice@example.com"] # Clear notes notes_scaffold.clear_notes()
State Structure class NotesState ( BaseModel ): notes: list[ str ] = [] categories: dict[ str , list[ str ]] = {} last_updated: datetime = None
FileManager Track file operations and maintain file system context.
Features
Operation tracking : Monitors read, write, delete operationsWorking directory : Tracks current directoryFile history : Maintains recent file access logRelationship mapping : Understands file dependencies
Usage agent = Agent( provider = "openai:gpt-4" , enable_scaffolds = True ) # Scaffold tracks file operations automatically agent.call( "Read config.json" ) agent.call( "Write output to results.txt" ) # Access file history files = agent.scaffolds[ "files" ] print (files.state.recent_files) # ["config.json", "results.txt"] # Working directory awareness print (files.state.working_directory) # "/home/user/project"
Operations # Track file operation files.track_file_operation( "read" , "data.csv" ) # Get recent files recent = files.get_recent_files( limit = 10 ) # Clear history files.clear_history()
State Structure class FileManagerState ( BaseModel ): recent_files: list[ str ] = [] working_directory: str = "." file_operations: list[ dict ] = []
ShellScaffold Command execution history and environment tracking.
Features
Command history : Tracks executed commandsExit codes : Monitors success/failureEnvironment tracking : Current directory, environment variablesOutput capture : Stores command output
Usage agent = Agent( provider = "openai:gpt-4" , enable_scaffolds = True ) # Scaffold tracks commands agent.call( "Run: npm install" ) agent.call( "Execute: pytest tests/" ) # Access history shell = agent.scaffolds[ "shell" ] print (shell.state.command_history) # [("npm install", 0), ("pytest tests/", 0)] # Check last command last_cmd, exit_code = shell.state.command_history[ - 1 ] print ( f "Last: { last_cmd } , Exit: { exit_code } " )
Operations # Track command shell.track_command( "git status" , exit_code = 0 ) # Get command history history = shell.get_command_history( limit = 20 ) # Clear history shell.clear_history()
State Structure class ShellState ( BaseModel ): command_history: list[tuple[ str , int ]] = [] working_directory: str = "." environment: dict[ str , str ] = {}
Disabling Built-in Scaffolds # Disable all built-in scaffolds agent = Agent( provider = "openai:gpt-4" , enable_scaffolds = False ) # Selective enabling with custom scaffolds agent = Agent( provider = "openai:gpt-4" , scaffolds = [MyCustomScaffold] # Only custom scaffolds )
What’s Next?
Creating Scaffolds Build your own custom scaffolds
Scaffold IPC Learn scaffold communication
