Complexity Mitigator

Complexity Mitigator

Intent

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

Core Mindset

• Keep essential complexity, vaporize the incidental.
• There is no silver bullet refactor; identify the dominant source of understanding cost before prescribing moves.
• 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, required state transitions, and irreducible external conformity/change pressure (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.

Brooks Lens (No Silver Bullet)

• Do not assume one move (extract, rename, state machine, types) will dissolve the whole problem.
• Ask four questions before recommending a cut:
  • Complexity: is the code hard because the real state space is large and interlocked?
  • Conformity: is the code hard because it must match awkward external APIs, schemas, laws, or legacy behavior?
  • Changeability: is the code hard because the surrounding requirements or extension pressure are genuinely moving?
  • Invisibility: is the code hard because intent is split across overlapping views (control flow, data flow, ownership, lifecycle, dependency)?
• Prefer recommendations that expose these constraints over recommendations that merely rearrange syntax.

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.
• The real question may be whether the complexity is in the code or in the requirements/boundaries the code must conform to.

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)
  • External conformity burden (legacy behavior, API/schema/policy obligations)
  • Change pressure (how much of the branching exists to preserve extension points or evolving cases)
  • Views to reconcile (control/data/lifecycle/ownership spread across multiple representations)
• 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, external conformity/change burden, and 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.
  • Do not flatten away required protocol steps, compatibility branches, or lifecycle edges; if they are essential, make them explicit instead.
• 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 external constraints remain essential versus which ones became localized
  • 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: ...
• Conformity/change pressure: ...
• 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.

Converted and distributed by TomeVault — claim your Tome and manage your conversions.