skills/tkersey/dotfiles/complexity-mitigator

complexity-mitigator

SKILL.md

Complexity Mitigator

Intent

Reduce incidental complexity (understanding cost) while preserving essential domain meaning.

Core Mindset

  • Keep essential complexity, vaporize the incidental.
  • Optimize for reader comprehension first, then for extraction.
  • Minimal incision, maximal precision: change only what reduces cognitive load.
  • Prefer boring, local clarity over cleverness.
  • Reduce "understanding cost": fewer branches to hold in mind, fewer places to jump, fewer states to simulate.

Epistemic Status (Heuristics, Not Laws)

  • The playbook below is a set of defaults, not guarantees.
  • There is no general proof that any single move always reduces complexity; validate locally.
  • When you break a default (e.g., extract before flatten), state the reason (what it unlocks).

Definitions (Essential vs Incidental)

  • Essential complexity: domain rules, invariants, boundaries, and required state transitions (simplifying it changes correct behavior or meaning).
  • Incidental (accidental) complexity: complexity introduced by implementation choices (simplifying it preserves behavior and clarifies intent).
  • Quick test (imperfect): if a reader must mentally execute the code to infer intent or allowed states, incidental complexity may be hiding the essential. Exception: some algorithms/concurrency require real simulation.

Engage When

  • A review stalls because readers can't follow the flow.
  • You need an explanation of what the code is doing (analysis-first) before changing anything.
  • You see deep nesting (>3 levels is a good heuristic), long if/else chains, or duplicated branching.
  • Progress requires cross-file hops or simulating shared/mutable state.

Guardrails

  • No file edits, no commits.
  • No running commands unless explicitly requested.
  • If expected behavior is unclear/product-sensitive, stop and ask.
  • If you suspect crash/corruption risk, recommend $fix.

Quick Scan (Cognitive Heat Read)

  • Measure (rough, not academic):
    • Max nesting depth
    • Branch count (if/else/switch/ternary)
    • Boolean soup count (booleans/flags that gate behavior, especially combined)
    • Cross-file hops (distinct definitions you must open to understand)
    • State to simulate (mutable vars, implicit globals, order dependencies)
  • Call out hotspots in one line each: path:line - [metrics] - why it is hard.
  • Tag each hotspot: essential (domain) vs incidental (implementation) vs mixed (domain hidden by noise).
  • Separate essential domain logic from incidental implementation noise before proposing changes.
  • Treat metrics as proxies; do not optimize for the number if it harms locality or domain clarity.

Workflow

  1. Choose the slice: entrypoint, inputs, outputs, state.
  2. Heat read: name hotspots and what makes them hard.
  3. Trace behavior (if meaning is unclear): happy path + key failure paths; call out mutations/IO.
  4. Verdict: separate essential domain logic from incidental implementation noise.
  5. Simplify in order (default): flatten -> rename -> extract (do not extract until flatten/rename reveals stable shapes).
  6. Options: rank by effort vs impact and state the smallest viable cut.
  7. Sketch: show the improved structure (types + flow), not the full implementation.
  8. TRACE: cite which letters are satisfied and which are currently violated.

Standard Playbook (Flatten -> Rename -> Extract)

  • Flatten:
    • Lead with guard clauses and early returns; keep the happy path linear.
    • Split nested conditionals into separate paths (small helpers or separate functions per path); keep helpers close to avoid extra cross-file hops.
    • Make temporal coupling explicit (state machine / explicit step enum) when ordering materially affects correctness.
  • Rename:
    • Replace vague verbs (process, handle, do) with domain actions; align nouns with domain entities.
    • Fix boolean naming (prefer positive, avoid double negatives); eliminate boolean-flag arguments when possible.
    • Move meaning into data: enums / tagged unions / option objects over multiple booleans (when it reduces branching or invalid states).
  • Extract (Rule of Three):
    • Split mixed responsibilities (parse vs validate vs decide vs effect).
    • Convert repeated branching into data-driven dispatch (tables, handler maps, pattern matching).
    • Extract only stable, repeatable concepts; Rule of Three is a heuristic (exceptions exist).

Option Ranking Rubric

  • Effort: tiny (rename/guard), small (split function), medium (introduce enum/table), large (module boundary / state machine).
  • Impact: reduces branching, reduces cross-file hops, reduces state to simulate, clarifies invariants.

What Counts as Evidence (Local, Not Global)

  • Prefer local, checkable evidence over universal claims.
  • Use before/after indicators where possible:
    • Nesting/branching/flags/hops/state-to-simulate (from the heat read)
    • Which invariant becomes explicit (type/constructor/assertion/test)
    • What tradeoff you accepted (e.g., more functions in exchange for linear flow)

Output Format

0) Slice

  • Entrypoint: ...
  • Inputs/outputs/state: ...

1) Heat Read (hotspots)

  • path:line - ...

1.5) Behavior Trace (optional)

  • Happy path: ...
  • Failure paths: ...
  • Mutations/IO: ...

2) Essential vs Incidental

  • Essential: ...
  • Incidental: ...

3) Options (ranked by effort vs impact)

  1. Smallest viable cut: ...
  2. ...
  3. ...

4) Sketch

// minimal illustrative snippet

5) TRACE

  • Satisfied: ... (letters your recommended structure improves)
  • Violated: ... (letters the current code is failing)

Why TRACE Is Part of Complexity Mitigation

  • In this skill, treat "complexity" primarily as understanding cost (not performance or operational complexity).
  • TRACE is the lens that prevents fake simplifications and makes tradeoffs explicit:
    • T (Type): can remove invalid states from consideration; over-modeling can also add noise.
    • R (Readability): reduces naming/structure friction that feels like complexity.
    • A (Atomic): separates decide vs do; mixed responsibilities often create incidental complexity.
    • C (Cognitive): directly targets nesting/branching/state simulation.
    • E (Essential): checks that you are deleting implementation noise, not deleting domain meaning.
  • Using TRACE makes the mitigation outcome checkable: "which understanding costs went down, and what got traded off?"

TRACE Quick Reference

  • T (Type): invalid states are unrepresentable; constraints live in types/constructors (keep the type model minimal).
  • R (Readability): intent is obvious from names and locality.
  • A (Atomic): one responsibility per unit; decisions separate from effects (avoid scattering logic across too many tiny units).
  • C (Cognitive): low nesting/branching; minimal state simulation.
  • E (Essential): code expresses only the domain-required complexity.

Invariant Guidance

Use when missing invariants block simplification.

  • Ask for or infer: state transitions, allowed/forbidden states, ownership/immutability, error handling boundaries.
  • Identify the smallest invariant that unlocks flattening (e.g., "state X implies Y").
  • If invariants are unknown, recommend adding assertions or making them explicit in types.

Footgun Checklist

Use when confusing APIs or naming cause misuse.

  • Hidden side effects or stateful globals
  • Non-obvious preconditions or order dependencies
  • Boolean parameters with inverted meaning
  • Silent defaults or magic values
  • Similar names for different concepts
  • Error handling that is inconsistent or implicit

Escalation

  • If repeated algebraic shapes or composable pipelines appear, consider switching to the Universalist skill and framing a minimal algebra + laws.
  • If the user wants implementation, escalate to $fix.
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