feat: Extends performance domain with anti-pattern scanning skills

[MajorLift]

Motivation

This PR adds review-time checks for React effect antipatterns and for the Redux selector antipatterns that cause render cascades. A selector that returns a fresh reference on every call raises no build error, fails no test and draws no user report, so it ships unless a review looks for it.

Overview

Extends the performance domain with two scan skills and the three knowledge files they cite. Both skills carry metamask-extension and metamask-mobile overlays.

• effect-antipattern-scan reviews PR diffs that add or modify useEffect for the effect antipatterns.
  • domains/performance/knowledge/effect-antipatterns.md: the platform-agnostic taxonomy of useEffect patterns that cause unnecessary renders, memory leaks or race conditions.
• selector-antipattern-scan reviews and diagnoses Redux selector antipatterns that cause render cascades, before and after merge.
  • domains/performance/knowledge/selector-antipatterns.md: the platform-agnostic taxonomy of selector patterns that break memoization.
  • domains/performance/knowledge/render-cascade.md: how one state change triggers several re-render cycles.
• The mobile performance skill gains mm-selector-cascade, mm-state-normalization and mm-useeffect-antipatterns. These and mm-selector-memoization map the knowledge-file patterns onto the mobile codebase instead of redefining them.

Not covered: neither scan checks renderItem identity instability, and neither scan's overlays mention FlatList or FlashList.

Sources: Frontend Performance Optimization Guidelines (MetaMask/contributor-docs#159).

[MajorLift]

Context budget

What this PR costs an agent, measured from an install rather than read from the diff. Three tiers, and only the first is unavoidable.

Skill	Frontmatter	Selected	+ refs & knowledge
data-analysis	221 chars	~1,428 tok	~1,428 tok
effect-antipattern-scan	89 chars	~1,193 tok	~1,193 tok
extension-profiling	134 chars	~680 tok	~680 tok
react-render-delta	780 chars	~1,938 tok	~1,938 tok
selector-antipattern-scan	100 chars	~2,510 tok	~2,510 tok
benchmark-design	109 chars	~882 tok	~882 tok

Frontmatter is the only tier paid unconditionally — every agent loads it on every run once the skill is installed, used or not, because it is what the agent reads to decide relevance. The 28 skills across the eleven open skill PRs sit at a median of ~1,716 tokens selected and ~1,860 with references followed. All are within the 1,536-character description budget.

Selected is paid only when the agent picks the skill. + refs & knowledge is the ceiling if every bundled reference is then read; it is a worst case, not an expectation.

Method

tools/install --repo metamask-extension --maturity experimental against this branch at c18c751a7, measured per installed skill directory. Repo overlays are merged into the emitted SKILL.md, so they land in the selected tier rather than being missed by a source-byte count. Token figures are bytes/4 — a proxy for scale, not accounting.

These figures are pinned to the commit above and drift on every push; #96 tracks automating them.