Pre Modification Check

Pre-Modification Check with Repowise

Before modifying files in a Repowise-indexed codebase, assess the impact.

Before editing a file

Call get_risk(targets=["path/to/file.py"]). Per file it returns hotspot_score, trend, risk_type, impact_surface (top 3), dependents_count, co_change_partners, primary_owner, bus_factor, test_gap, and security_signals. Read it for:

• Bug-fix history (defect_profile) — present only on files with counted fixes: fix_count over the trailing 6 months, last_fix_days_ago, a bug_magnet flag for sustained recent fix pressure, and top_symbols (the per-symbol counts are approximate — read them as "mostly here"). A file that keeps getting fixed is the strongest single signal that the next edit breaks something; lead with it.
• Hotspot status (hotspot_score, trend) — high-churn × complex? Extra care needed.
• Dependents (dependents_count, impact_surface) — how wide is the blast radius?
• Co-change partners — files that change together with this one (often without an import link); you may need to update them too.
• Ownership / bus factor — who owns it, and whether a single author maintains it.
• Test gap & security signals — flag untested or security-sensitive files before touching them.

When modifying multiple files

Batch all targets into one call: get_risk(targets=["file1.py", "file2.py", "module/"]).

When to warn the user

If get_risk shows:

• A defect_profile with bug_magnet set — say so plainly: this file has been fixed repeatedly and recently
• Hotspot score above 90th percentile — mention this is a frequently-changed, high-risk file
• More than 10 dependents — list the top dependents; API changes here will break consumers
• Bus factor of 1 — note that a single person maintains this code
• Risk type is "bug-prone" or "high-coupling" — flag explicitly before making changes

Before refactoring or moving code

Call get_context(targets=["file.py"]) first to understand the full context: what uses this file, what decisions govern it, and why it's structured this way. This prevents accidentally violating architectural decisions.

For a heavy refactor, also call get_health(targets=["file.py"]) — the marker findings (complexity, deep nesting, low cohesion, duplication) tell you what to improve while you're in there, and give you a before/after score.

Error handling

If get_risk returns a tool error, the MCP server may not be running. Proceed with the modification but note that risk assessment was unavailable.