Memtrace Cochange

Overview

Find files that historically co-change with a target symbol or file path — ranked by co-occurrence frequency across git episodes. Surfaces behavioral coupling the static call graph cannot see.

get_impact answers "who calls this?" (structural). get_cochange_context answers "what files always move when this moves?" (historical, file-level).

They are complementary. A file with no call-graph edges to the target can still be a strong cochange partner if it's always modified alongside it in every commit.

Parameter types: Numbers (limit, window_days, etc.) must be JSON numbers — not strings.

Required parameters

{
  "repo_id": "memdb",
  "target": "execute",
  "limit": 10,
  "window_days": 30
}

Full parameter spec for every Memtrace tool: references/mcp-parameters.md (bundled at the memtrace-skills plugin root).

Output

{
  "cochanged_files": [
    {
      "file_path": "src/order/types.rs",
      "cochange_count": 8,
      "last_cochanged_at": "2026-04-13T10:43:00Z"
    }
  ],
  "target_files": ["src/order/service.rs"]
}

There is no cochanges[] with symbol names — results are file-level.

Steps

1. Identify the target

Use find_symbol if needed. Pass the symbol name or a file_path as target.

2. Call get_cochange_context

See required parameters above.

3. Interpret results

High cochange_count on a file → strong historical coupling. When you modify the target, review those files too — even without direct call-graph edges.

4. Cross-reference with call graph

For symbols in cochanged files, optionally run get_impact(target=...):

Use Cases

• Before modifying a symbol — get blast awareness beyond what get_impact shows
• Incident investigation — when get_impact doesn't explain the blast radius, check cochange history
• Code review — verify that a PR touched all historically-coupled partners
• Refactoring — discover implicit coupling before extracting a module

Common Mistakes