impact-matrix

name	impact-matrix
description	This skill should be used when the user asks to prioritize performance issues, says "which fix should I do first", "rank these findings", "what's the highest impact change", "create a priority matrix", "complexity vs impact", "what should we focus on", "help us decide what to fix next sprint", "triage these issues", or provides a list of performance findings that need to be ranked. Applies a structured Complexity × Impact matrix and produces a prioritized action plan.
argument-hint	[list of findings to prioritize]
allowed-tools	Read

Impact Matrix

Complexity × Impact Prioritization Matrix

Scoring Dimensions

Score each finding on two dimensions (1–3 scale):

Impact — user or business effect if fixed

Score	Meaning
3	Directly visible to users or causes SLO breach
2	Measurable improvement but not directly user-facing
1	Minor improvement; internal or technical benefit only

Complexity — effort required to implement the fix

Score	Meaning
1	<1 day: config change, add index, fix cache header
2	1–5 days: refactor one component, add cache layer, pool objects
3	>1 sprint: architectural change, data model migration, platform upgrade

Priority score = Impact ÷ Complexity (higher = act sooner)

Quadrant Map

         HIGH IMPACT (3)
              │
  Quick Wins  │  Strategic Projects
  Impact 3    │  Impact 3
  Complexity 1│  Complexity 3
  ────────────┼────────────────────
  LOW         │                HIGH
  COMPLEXITY  │           COMPLEXITY
  ────────────┼────────────────────
  Low-Hanging │  Avoid / Defer
  Fruit       │  Impact 1
  Impact 1-2  │  Complexity 3
  Complexity 1│
              │
         LOW IMPACT (1)

• Quick Wins → Ship immediately; highest ROI
• Strategic Projects → Schedule in roadmap; break into milestones
• Low-Hanging Fruit → Batch in a cleanup sprint
• Avoid / Defer → Do not prioritize; revisit if scale or impact changes

Scoring Template

When given a list of findings, produce this prioritized table:

| # | Finding                        | Impact | Complexity | Score | Quadrant          |
|---|--------------------------------|--------|------------|-------|-------------------|
| 1 | Add index on orders.user_id    |   3    |     1      |  3.0  | Quick Win         |
| 2 | Migrate to async I/O           |   3    |     3      |  1.0  | Strategic Project |
| 3 | Enable gzip on API responses   |   2    |     1      |  2.0  | Low-Hanging Fruit |
| 4 | Rewrite ORM to raw SQL         |   1    |     3      |  0.3  | Avoid / Defer     |

Sort descending by Score. Explicitly call out all Quick Wins as immediate actions.

Adjust presentation based on the target audience:

• Developer: Include file/function reference per finding; note PR size estimate
• Perf Engineer: Add "measurement required" column; flag items needing a benchmark before scoring
• DevOps: Flag items requiring infrastructure changes; note deployment risk per item
• Leadership: Replace complexity score with "Estimated effort in weeks"; replace impact score with a user impact statement

Common Scoring Pitfalls

• Don't let complexity dominate: A 3-day fix with p99 latency impact beats a 1-hour fix with cosmetic gain
• Re-score after dependencies: If Fix A removes the cause of Fix B, score them as a unit
• Decay findings over time: Re-score as scale changes — an issue that was Impact 3 at 10k users may be Impact 2 at 1M
• Validate with measurement: Scores are estimates; build a benchmark before committing to large-complexity items
• Avoid premature optimization: Score 1/1 findings are fine to batch, but never let them crowd out higher-priority work

Tiebreaker Rules

When two findings have the same score:

1. Prefer the one with lower risk (fewer systems touched, easier rollback)
2. Prefer the one that unblocks other fixes
3. Prefer the one with existing test coverage (safer to change)

After presenting the matrix, output: "Run /perfmind:report [role] to generate a role-specific report using these findings."