Lattice - Large File Analysis

Use the Lattice MCP tools to analyze files that are too large to read directly. Lattice stores query results server-side and returns compact handle stubs, achieving 97%+ token savings.

When to Use

• File is larger than 500 lines (for smaller files, use Read directly)
• You need multiple searches on the same file
• You're extracting or aggregating structured data (counts, sums, patterns)
• You're doing exploratory analysis and don't know what you're looking for
• You want to avoid hallucination on factual queries about file contents

Core Workflow

The standard workflow is: load → query → expand → close

1. lattice_load — Open the file (starts a session)
2. lattice_query — Run Nucleus S-expression commands (returns handle stubs like $res1)
3. lattice_expand — Inspect actual data from a handle when you need to see contents
4. lattice_close — End the session when done

Efficiency Tips

• Chain operations in sequence rather than making many independent queries. Use RESULTS to refer to the previous result and build a pipeline in a single query session.
• Start broad, then narrow: grep first, then filter, then count/sum.
• Only expand when needed: Handle stubs give you counts and previews — expand only when you need to see actual data for decision-making.
• Prefer (count RESULTS) or (sum RESULTS) over expanding and counting client-side.

Nucleus Command Reference

Search

(grep "pattern")              ; Regex search — returns handle to matching lines
(fuzzy_search "query" 10)     ; Fuzzy match — top N results by relevance
(lines 10 20)                 ; Get specific line range (start end)

Transform

(filter RESULTS (lambda x (match x "pattern" 0)))   ; Keep matching items
(map RESULTS (lambda x (match x "(\\d+)" 1)))       ; Extract regex group from each item

Aggregate

(count RESULTS)               ; Count items (returns scalar directly)
(sum RESULTS)                 ; Sum numeric values (auto-extracts numbers)

Extract

(match str "pattern" 1)       ; Extract regex capture group from a string

Code & Document Symbols (for .ts, .js, .py, .go, .rs, .md, etc.)

(list_symbols)                ; List all functions, classes, methods, headings, etc.
(list_symbols "function")     ; Filter by kind: "function", "class", "method", "interface", "type"
(get_symbol_body "funcName")  ; Get full source code of a symbol
(find_references "identifier"); Find all usages of an identifier

Variable Bindings

• RESULTS — Always points to the last array result. Use this in queries to chain operations.
• _1, _2, _3, ... — Results from turn N. Use to reference older results in queries.
• $res1, $res2, ... — Handle stubs. Use these ONLY with lattice_expand, NOT in queries.

Complete Workflow Example

Task: Find and count timeout errors in a log file

1. Load the document:

   lattice_load("/path/to/server.log")
   

   → Loaded: 15,234 lines, 2.1 MB

2. Search for errors:

   lattice_query('(grep "ERROR")')
   

   → $res1: Array(342) [2024-01-15 ERROR: Connection timeout...]

3. Filter for timeouts:

   lattice_query('(filter RESULTS (lambda x (match x "timeout" 0)))')
   

   → $res2: Array(47) [2024-01-15 ERROR: Connection timeout...]

4. Count them:

   lattice_query('(count RESULTS)')
   

   → Result: 47

5. Inspect a sample if needed:

   lattice_expand("$res2", limit=5)
   

   → Shows first 5 actual timeout error lines

6. Close when done:

   lattice_close()
   

Code Analysis Workflow

Task: Understand a large TypeScript file

1. Load and list symbols:

   lattice_load("/path/to/large-module.ts")
   lattice_query('(list_symbols)')
   

   → $res1: Array(45) [function handleRequest, class Router, ...]

2. Get a specific function:

   lattice_query('(get_symbol_body "handleRequest")')
   

   → Returns full source code of the function

3. Find all references:

   lattice_query('(find_references "handleRequest")')
   

   → $res2: Array(8) [line 45: handleRequest(req), ...]