# LLM-Ergonomic Patch Content Implementation Summary
## What Was Built
### 1. Query Structure Tool (`obsidian_query_structure`)
A new tool that allows LLMs to inspect document structure before making modifications:
- **Purpose**: Eliminates ambiguity by letting LLMs see all headings, blocks, and structure
- **Features**:
- Returns full heading paths (e.g., `["Implementation", "Overview"]`)
- Adds occurrence numbers for duplicate headings
- Provides line numbers for precise targeting
- Includes metadata like content presence and children count
### 2. Patch Content V2 Tool (`obsidian_patch_content_v2`)
A redesigned content modification tool with LLM-ergonomic API:
- **Explicit Operations**: Clear operation types (`replace`, `insert`, `update_frontmatter`)
- **Deterministic Targeting**:
- Heading paths with occurrence numbers
- Block IDs for absolute precision
- Pattern matching with regex support
- **Structured Errors**: Machine-readable error codes with suggestions
## Key Design Decisions
### 1. Explicit Over Simple
Instead of simplifying for humans, we made everything explicit for LLMs:
```typescript
// Not this (ambiguous):
{ heading: "Overview", insertAfter: true }
// But this (deterministic):
{
operation: {
type: "insert",
insert: {
location: {
type: "heading",
heading: {
path: ["Implementation", "Overview"],
occurrence: 2
},
position: "after"
}
}
}
}
```
### 2. Query-First Workflow
LLMs should query structure before modifying:
1. Query document structure
2. Analyze results to find exact targets
3. Build unambiguous operations
4. Handle errors programmatically
### 3. Backward Compatibility
- Original `patch_content` remains available
- New tools are additions, not replacements
- Migration path provided in documentation
## Implementation Status
### Completed
- ✅ Query structure tool with heading/block detection
- ✅ Basic patch content v2 with replace/insert operations
- ✅ Structured error responses
- ✅ Documentation and examples
- ✅ TypeScript types and build configuration
### Simplified for Demo
- Frontmatter operations (basic implementation)
- Section-scoped replacements (marked as not implemented)
- Full heading path resolution (simplified version)
### Future Enhancements
- Complete document parsing with AST
- Full section-aware operations
- Advanced frontmatter merge/append operations
- Pattern-based insertion
- Block reference creation
## Why This Approach Works
### For LLMs
1. **No Ambiguity**: Every reference is deterministic
2. **Predictable**: Explicit parameters mean clear outcomes
3. **Recoverable**: Structured errors enable retry strategies
4. **Validatable**: Schema expresses all constraints
### For MCP
1. **Stateless**: Each operation is self-contained
2. **REST-Compatible**: Maps to existing Obsidian REST API
3. **Extensible**: Easy to add new operation types
4. **Tool Composition**: Query + Patch work together
## Usage Pattern
```typescript
// 1. LLM queries structure
const structure = await query_structure({
filepath: "doc.md",
query: { type: "headings" }
});
// 2. LLM finds target
const target = structure.headings.find(h =>
h.text === "Budget" && h.path.includes("Planning")
);
// 3. LLM builds operation
await patch_content_v2({
filepath: "doc.md",
operation: {
type: "insert",
insert: {
content: "New content",
location: {
type: "heading",
heading: {
path: target.path,
occurrence: target.occurrence
},
position: "after"
}
}
}
});
```
## Conclusion
This implementation demonstrates how to design APIs specifically for LLM consumers rather than humans. By embracing explicitness and structure, we create tools that LLMs can use reliably and deterministically.
