🧠 Agent Template Requirements (v0.1)

Overview

This document defines the foundational requirements for a modular, extensible agent template — designed to support AI-guided workflows with web interaction, local file I/O, and memory integration. The agent will serve as a scaffold for building more complex cognitive systems (e.g., Igor) and will be designed with security, modularity, and introspectability in mind.

Core Capabilities

1. Web Interaction Layer ("Hands")

• Use Selenium (or optionally Pywinauto) to:
• Navigate and interact with web pages
• Simulate user actions (clicks, typing, scrolling)
• Handle dynamic content and form submissions
• Optional: Extend to native Windows apps via Pywinauto

2. Local File I/O (Sandboxed)

• Read and write files within a restricted directory tree
• Support:
• Reading structured files (e.g., JSON, CSV)
• Writing AI-generated outputs (e.g., reports, logs)
• Triggering downloads via browser automation
• Enforce path whitelisting or containerized sandboxing

3. JSON Chunking for Upstream AI

• Parse local JSON files
• Break into semantically meaningful chunks
• Stream or batch-send to upstream AI for processing
• Preserve context and traceability of source data

4. File Download Handling

• Detect and manage downloads initiated by AI (e.g., via browser or direct link)
• Store in designated sandboxed directory
• Log metadata (source, timestamp, file type)

5. Memory and Database Integration

• Support plug-and-play memory backends:
• Relational (e.g., SQLite, Postgres)
• Vector (e.g., Chroma, Weaviate)
• Key-value (e.g., Redis, DuckDB)
• Enable:
• Episodic memory (interaction logs, state snapshots)
• Semantic memory (facts, concepts, embeddings)
• Guiding principles (core cognitive habits)

Optional / Future Layers (for consideration)

Layer	Description
Logging + Replay	Full trace of actions, inputs, outputs, and memory access
Capsule Execution Framework	Modular, composable task units with pause/resume/debug
Error Recovery	Retry logic, fallback strategies, and exception handling
Prompt Guardrails	Sanitize inputs/outputs to prevent prompt injection
Memory Access Tracing	Track which memories were read/written per task
Task Orchestration	Queueing, scheduling, and multi-agent coordination
Authentication Management	Secure credential handling and session persistence
Human-in-the-Loop Hooks	Manual override, approvals, or feedback injection

Design Principles

• Modularity: Each capability should be encapsulated in a reusable capsule or module
• Security: File and web access must be sandboxed and auditable
• Transparency: All actions should be logged and explainable
• Extensibility: Designed to evolve with Igor’s growing cognitive architecture