Agentic Tools

IWE provides CLI commands that turn your personal knowledge graph into AI memory. These tools give AI agents the same navigation capabilities you have — discovering entry points, following relationships, and retrieving knowledge with appropriate context.

The Context Bridge

When AI agents work with traditional files, they face three problems:

1. Fragmented context — Knowledge scattered across files with no structure
2. Retrieval ineffectiveness — Search finds text but misses relationships
3. No memory iteration — Each conversation starts from scratch

IWE solves this by giving AI agents real navigation capability. Your knowledge graph isn’t just text to search through — it’s a structure AI can traverse, following the same relationships you created.

This is the context bridge: your personal knowledge graph that both you and AI can navigate and build upon.

How AI Navigates Your Knowledge

AI agents use these commands to collaborate with your knowledge:

Navigation commands:

• iwe find — Discover entry points with fuzzy search
• iwe retrieve — Get content with graph expansion and context
• iwe tree — Display document hierarchy as navigable structure

Analysis commands:

• iwe stats — Generate knowledge base statistics

Refactoring commands:

• iwe extract — Extract sections to new documents
• iwe inline — Inline referenced content
• iwe delete — Delete documents and clean up references
• iwe rename — Rename documents and update references

Together, these commands let AI:

• Start from any topic and discover related knowledge
• Follow graph relationships to build understanding
• Retrieve exactly the context needed for a task
• Navigate your knowledge the way you do
• Refactor and reorganize knowledge programmatically

Available commands

Typical agent workflow

iwe find "authentication" --roots -f keys

iwe retrieve -k authentication -d 2 -c 1

iwe retrieve -k login-flow -e authentication

1. Find entry points using iwe find with fuzzy search
2. Retrieve content with appropriate depth and context
3. Follow relationships by retrieving linked documents
4. Exclude known content to avoid duplication

Output formats

Both commands support multiple output formats:

Integration examples

Claude Code / MCP integration

iwe find --roots -f json | jq '.results[].key'

iwe retrieve -k "$KEY" -d 1 -c 1

Building context for LLMs

iwe find "$QUERY" -l 5 -f keys | while read key; do
  iwe retrieve -k "$key" -d 0 -c 0 --dry-run
done

iwe retrieve -k "$SELECTED_KEY" -d 2 -c 1

Why Graph Structure Matters

Traditional file search treats your knowledge as a bag of text. IWE’s graph structure enables real navigation:

• Relationships are explicit — Links between documents create navigable paths
• Context is preserved — Parent and child documents provide understanding
• Structure is shared — AI follows the same paths you created
• Memory accumulates — Knowledge builds on itself over time

Learn more about the underlying concepts in The Context Bridge.