Agent skill
leindex-code
Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 82% savings (balanced mode) with semantic completeness.
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Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/tldr-code
SKILL.md
LeIndex-Code: Complete Reference
Token-efficient code analysis with 82% token savings (balanced mode) while preserving semantic completeness for LLM usage.
Quick Reference
| Task | Command |
|---|---|
| Context extraction | from maestro.leindex import ContextExtractor |
| Semantic search | from maestro.leindex import semantic_search |
| AST analysis | from maestro.leindex import ASTAnalyzer |
| Call graph | from maestro.leindex import CallGraphAnalyzer |
Modes
Balanced Mode (Default) - 82% savings, LLM Actionable
Use for: Code generation, refactoring, implementation
python
from maestro.leindex import ContextExtractor
extractor = ContextExtractor(mode='balanced') # Default
result = extractor.extract_for_file('src/api.py')
print(f"Savings: {result.savings_percent:.1f}%")
print(result.context.to_llm_string())
# Output includes:
# L119: analyze_file(file_path: str, include_call...) -> ContextExtractionResult
# L136: semantic_search(query: str, project_path..., limit: int)
Ultra Mode - 98% savings, Exploration Only
Use for: Code exploration, search, impact analysis
python
extractor = ContextExtractor(mode='ultra')
result = extractor.extract_for_file('src/api.py')
# Output:
# fn:analyze_file build_semantic_index get_token_savings
# (No signatures, NOT actionable for code generation)
Token Efficiency Comparison
| Mode | Savings | Semantic Quality | LLM Actionable | Use Case |
|---|---|---|---|---|
| Raw | 0% | Complete | ✓ Yes | Full file |
| Balanced | 82% | High | ✓ Yes | Code generation |
| Ultra | 98% | Low | ❌ No | Exploration only |
Key Insight: Balanced mode at 82% savings is the OPTIMAL balance for LLM-assisted coding. Ultra mode sacrifices too much semantic information (no signatures, no line numbers, no types) for LLM to accurately use the code.
Python API
python
from maestro.leindex import (
# 5-layer analyzers
ASTAnalyzer,
CallGraphAnalyzer,
CFGAnalyzer,
DFGAnalyzer,
SlicingAnalyzer,
# Context extraction
ContextExtractor,
get_relevant_context,
get_context_for_prompt,
# Semantic search
SemanticIndex,
semantic_search,
build_semantic_index,
# Memory integration
LeIndexMemoryBridge,
get_leindex_memory_bridge,
)
# Example: Get token-efficient context (balanced mode)
extractor = ContextExtractor(mode='balanced')
result = extractor.extract_for_file('maestro/leindex/__init__.py')
print(f"Savings: {result.savings_percent:.1f}%")
print(f"Quality: {result.get_quality_report()}")
# Example: Semantic search
results = semantic_search("authentication functions", "/path/to/project")
for entity, score in results:
print(f"{entity.name} in {entity.file} (score: {score:.2f})")
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