memtrace-change-impact-analysis

name

memtrace-change-impact-analysis

description

Compute what a planned source-code change will break — blast radius, affected processes, cross-repo callers, temporal stability, and Cortex decision-memory constraints — and produce a risk-rated change plan. Use for multi-symbol or multi-part edits, refactors, API changes, renames, removals, PR reviews, or risk assessments that need a plan; for one symbol's raw blast radius, call get_impact directly. Do not manually grep references or browse files for impact; use Memtrace graph context, change history, and decision recall/provenance.

Overview

Pre-change risk assessment workflow. Before modifying code, this workflow maps the full blast radius, identifies affected processes, checks recent change history for instability signals, checks Cortex decision memory for recorded decisions/bans/contracts, and produces a risk-rated change plan.

Use this workflow when the change spans multiple symbols or needs a risk-rated plan. For a quick raw upstream/downstream radius around one known symbol, call get_impact directly.

Steps

1. Identify what's being changed

Find the target symbol(s):

• Use find_symbol if the user named specific functions/classes
• Use find_code if the user described behaviour ("the authentication middleware")

Collect symbol names (name, scope_path, file_path) for all targets — graph tools use names, not internal IDs.

2. Get 360° context for each target

For each symbol, call get_symbol_context (repo_id, symbol, file_path):

• Direct callers and callees
• Community membership (which module is this in?)
• Process membership (which execution flows does this participate in?)
• Cross-repo API callers (is this an endpoint called by other services?)

Decision: If cross-repo API callers exist, this change requires coordination with other teams. Flag this immediately.

3. Compute blast radius

For each target, call get_impact (repo_id, target) with direction: "both", depth: 5:

• Upstream impact: what depends on this symbol
• Downstream impact: what this symbol depends on
• Risk rating: Low / Medium / High / Critical

Decision:

Risk	Action
Low	Proceed with standard testing
Medium	Review all direct callers; test affected processes
High	Plan incremental migration; consider feature flags
Critical	Full migration strategy; backward-compatible changes required

4. Check Cortex decision memory

For each target or subsystem, call recall_decision("<target/subsystem/approach>"). If the graph result exposes a numeric symbol_id, also call why_is_this_here(symbol_id) and governing_contracts(symbol_id).

• Matching decision/ban/convention → include it in the plan before recommending a change.
• Decision you intend to rely on → run verify_intent(decision_id) first.
• CannotProve → record "no decision proven"; do not treat it as approval.

5. Check temporal stability

Call get_evolution (repo_id, from: "30d ago", mode: "compound"), then get_timeline on each target symbol (requires scope_path + file_path from find_symbol):

• Sparse timeline history + you're about to change it → structurally surprising; extra scrutiny warranted.
• Target appears in top_touched_symbols → high churn + high impact = volatile hotspot.

6. Map affected execution flows

From step 2, you already know which processes are affected. For critical changes, use analyze_relationships (repo_id, target) with query_type: "find_callers" at depth: 3 to trace the full transitive caller chain.

depth: 3 is a JSON number, not a string — the validator rejects "3". Full parameter spec for every Memtrace tool: references/mcp-parameters.md (bundled at the memtrace-skills plugin root).

7. Produce the risk assessment

Synthesize into a change plan:

1. Target(s) — what's being changed and where
2. Blast Radius — number of direct/transitive dependents, risk rating
3. Affected Processes — which execution flows will be impacted
4. Cross-Service Impact — any external callers or consumers
5. Stability Signal — sparse get_timeline history (stable) vs frequent appearance in top_touched_symbols (volatile)
6. Decision Memory — relevant decisions/bans/contracts, or CannotProve as unknown
7. Recommended Approach — based on risk and decision constraints: direct change, incremental migration, or backward-compatible evolution
8. Test Coverage — which callers/processes to verify after the change

Decision Points

Condition	Action
Risk = Critical	Recommend backward-compatible change + deprecation path
Cross-repo callers exist	Flag as requiring multi-service coordination
Symbol has sparse timeline but high impact	Extra review — this rarely changes; make sure the change is intentional
Multiple processes affected	List each affected flow; recommend testing each one
Symbol is a bridge point	Change may disconnect parts of the architecture — verify alternative paths exist
Cortex returns a held ban/contract	Do not recommend contradicting it without explicit user sign-off

Output

The workflow's artifact is the step-6 risk-rated change plan. Compact example:

Target: AuthService::validateToken (src/auth/service.ts)
Blast Radius: 4 direct / 23 transitive dependents — Risk: High
Affected Processes: login-flow, session-refresh
Cross-Service Impact: 2 cross-repo API callers — needs multi-service coordination
Stability Signal: appears in top_touched_symbols (volatile hotspot)
Recommended Approach: incremental migration behind a feature flag
Test Coverage: all 4 direct callers + both affected processes