kylesnowschwartz/simpleclaude/sc-think-functional

Think Functional

FP discipline for agent-assisted development. Not about switching languages — about structuring code so agents write it well and humans review it fast.

Why FP Matters for Agents

<thesis>

Agents are pattern matchers. They compress training data into a world model, then map between representations: f(pattern_in, context, constraints) => pattern_out. FP makes the patterns explicit.

</thesis>

The Reframe

When approaching any design decision:

Instead of: "What object/class should own this behavior?" Ask: "What's the pure transform, and where does the effect happen?"

Every function is one of three things:

The Toolkit

Apply these operations to any code design problem:

<operations>

Separate: Pure from Impure

Ask: "If I deleted every side effect from this function, what computation remains?"

That computation is your pure core. Extract it. The side effects become a thin shell that calls the pure function and does IO with the result.

BEFORE: fetchUser(id) { data = await fetch(url); return validate(data); }
AFTER:  validateUser(data) { ... }  // pure
        fetchUser(id) { data = await fetch(url); return validateUser(data); }  // edge

Push Effects Outward

Ask: "Can the caller handle this effect instead of the callee?"

Effects belong at the outermost layer possible. Pushing the read out of the callee turns the function pure and lets the caller — who already knows the context — supply the data.

// BEFORE: callee reads localStorage; can't be tested without a DOM mock
function renderTheme(): string {
  const prefs = JSON.parse(localStorage.getItem("prefs") ?? "{}");
  return prefs.dark ? "dark" : "light";
}
// AFTER: caller reads, callee computes; pure function, trivial test
function renderTheme(prefs: { dark?: boolean }): string {
  return prefs.dark ? "dark" : "light";
}
// at the edge:
const prefs = JSON.parse(localStorage.getItem("prefs") ?? "{}");
renderTheme(prefs);

Make Illegal States Unrepresentable

Ask: "Can the type system prevent this bug, or does it rely on runtime discipline?"

Three encodings cover most real bugs — branded types for confusable values, Result<T, E> for fallible computation, and exhaustive switch for finite sums.

// (a) Branded type + smart constructor — raw strings can't reach UserId-typed APIs
type UserId = string & { readonly __brand: "UserId" };
const UserId = (raw: string): UserId | null =>
  /^u_[a-z0-9]{8}$/.test(raw) ? (raw as UserId) : null;
// (b) Result<T, E> — failure is in the return type, not in exceptions
type Result<T, E> = { ok: true; value: T } | { ok: false; error: E };
const parseAge = (s: string): Result<number, "NaN" | "Negative"> => {
  if (s.trim() === "") return { ok: false, error: "NaN" }; // Number("") === 0 — guard first
  const n = Number(s);
  if (Number.isNaN(n)) return { ok: false, error: "NaN" };
  if (n < 0) return { ok: false, error: "Negative" };
  return { ok: true, value: n };
};
// (c) Exhaustive switch — adding a new variant becomes a compile error
type Shape = { kind: "circle"; r: number } | { kind: "square"; side: number };
const area = (s: Shape): number => {
  switch (s.kind) {
    case "circle": return Math.PI * s.r ** 2;
    case "square": return s.side ** 2;
    default: { const _: never = s; throw new Error(`Unhandled: ${JSON.stringify(_)}`); }
  }
};

Enforce Through Structure, Not Convention

Ask: "If an agent ignores my instructions, does the code still work correctly?"

Agents are lazy. They'll take shortcuts if shortcuts compile. Convention says "don't put side effects here." Structure says "this module physically cannot import the side-effect library." Prefer structure. Stack two real mechanisms — editor-time lint plus a build/CI graph check — so a violation fails before review.

The two configs below sketch the shape of those checks: a per-file glob, a list of forbidden imports, a list of forbidden globals, and a from/to graph constraint. Tooling syntax shifts between releases (ESLint v9 moved to flat config; the depcruise CLI changed across major versions), so verify the exact form against your toolchain's current docs rather than copy-pasting.

// .eslintrc.json — inside any *.pure.ts file, block effectful imports
// (modules) AND effectful globals (browser APIs the import rule cannot see).
{
  "overrides": [
    {
      "files": ["**/*.pure.ts"],
      "rules": {
        "no-restricted-imports": ["error", {
          "patterns": ["zustand", "zustand/*", "react", "react-dom",
                       "**/persistence/*", "**/effects/*"]
        }],
        "no-restricted-globals": ["error",
          "localStorage", "sessionStorage", "fetch",
          "document", "window", "navigator"
        ]
      }
    }
  ]
}

// .dependency-cruiser.cjs — graph-level rule, run as part of CI. Fails the
// build when any *.pure.ts file pulls in an effectful package or a
// persistence/effect directory, even if lint was bypassed locally.
module.exports = {
  forbidden: [
    {
      name: "no-effects-in-pure",
      severity: "error",
      from: { path: "\\.pure\\.ts$" },
      to:   { path: "(node_modules/(zustand|react|react-dom)|/persistence/|/effects/)" }
    }
  ]
};

The naming convention (.pure.ts) and directory layout are organizational scaffolding — they give the lint and graph rules a stable target to match. Convention catches one agent on a good day; the lint rule catches every agent on every keystroke; the graph rule catches the violations that slip past lint and fails CI. Branded types do the same job at the value level — preventing pixel coords from reaching hex math without a runtime check.

Narrow the Interface

Ask: "What's the minimum this function needs to know?"

A function that takes the whole world hides its real input. Extract a pure core that names exactly what it consumes; let a thin shell handle the rest.

// BEFORE: 8 lines, mixes effect + computation, takes whole AgentState
function nextHexLabel(state: AgentState): string {
  if (!state.selected) return "";
  const hex = state.board.hexes[state.selected.hexId];
  if (!hex) return "";
  const n = hex.q + hex.r;                          // <-- the actual computation
  return `${hex.q},${hex.r} (#${n})`;
}
// AFTER: pure core takes only what it needs; edge shell does the lookup
const formatHexLabel = (hex: { q: number; r: number }): string =>
  `${hex.q},${hex.r} (#${hex.q + hex.r})`;          // pure, narrow input
function nextHexLabel(state: AgentState): string {  // 3-line edge shell
  const hex = state.selected && state.board.hexes[state.selected.hexId];
  return hex ? formatHexLabel(hex) : "";
}

</operations>

Applied to Stores (Zustand, Redux, etc.)

State management is where FP discipline pays off most in frontend code:

Store action template:

1. Read current state
2. Compute new state (call pure functions)
3. Single set() call
4. Return value for caller — no side effects

Applied to Handlers

Handlers dispatch on message type and perform effects. Use dependency injection to keep them testable:

interface HandlerDeps {
  getAgent: (id: string) => Agent | undefined;
  // inject only what's needed
}
function createHandler(deps: HandlerDeps): (msg: Message) => void

The handler factory is pure (given deps, returns a function). The deps are wired at the composition root. Testing injects mock deps without touching real stores.

File Organization

Make purity visible in the filesystem:

feature/
  types.ts          # Pure types, no runtime
  foo.pure.ts       # Pure transforms — agents write these freely
  fooStore.ts       # State transitions — review action shapes
  fooPersistence.ts # Edge effects — review carefully
  Foo.tsx           # UI — inherently impure, review interaction logic

The .pure.ts suffix signals to both agents and reviewers: this file has no side effects, is enforced by linting, and can be trusted if the types check.

Review Protocol

When reviewing agent-written code through an FP lens:

1. Architecture (composition): Read this carefully. Does the wiring make sense? Are effects at the edges?
2. Edge functions (IO, DOM, network): Read every line. These are where bugs live.
3. Pure functions: Check types match. Skim body. If types are right and tests pass, the implementation is almost certainly correct.
4. Test summaries: Are edge cases covered? Are pure functions tested with property-based or example-based tests?

Time allocation: 60% on composition + edges, 30% on tests, 10% on pure function bodies.

Anti-Patterns