Expressive TypeScript

Quick Guide: Write code that communicates its intent without requiring the reader to mentally simulate any of its parts. Apply the two-tier pattern: orchestrators at the top that read like pseudocode, pure functions at the bottom that each do one thing. Extract until the code reads like prose. Use utility libraries only when they genuinely improve readability over plain JS.

<critical_requirements>

CRITICAL: Before Using This Skill

All code must follow project conventions in CLAUDE.md (kebab-case, named exports, import ordering,

import type

, named constants)

(You MUST structure every non-trivial function as a two-tier orchestrator: guard clauses at the top, named function calls in the middle, assembly at the bottom -- NO inline data transformations in orchestrators)

(You MUST extract any expression that requires mental simulation to understand into a named function or named constant)

(You MUST name functions for WHAT they do, not HOW they do it --

isContentAddition(line)

checkLineStartsWithPlusButNotTriplePlus(line)

(You MUST read the existing code before refactoring -- understand the current structure, then improve it)

(You MUST prefer plain JS methods (

.map()

.filter()

.reduce()

</critical_requirements>

Auto-detection: orchestrator pattern, two-tier function, extract function, named predicate, named constant, readability refactor, expressive code, function decomposition, pure function extraction, readable TypeScript, guard clause, early return, flatten conditionals, discriminated union, exhaustive switch, as const satisfies, async orchestrator

When to use:

• Writing any function that mixes validation, transformation, and assembly logic
• Refactoring a function where you need to mentally simulate steps to understand the flow
• Naming predicates, constants, or transforms to communicate intent
• Deciding whether to use a utility library function or plain JS
• Decomposing a large function into orchestrator + pure helpers
• Reviewing code and finding blocks that require mental simulation
• Flattening deeply nested if/else blocks into guard clauses
• Writing async functions that orchestrate multiple independent operations
• Modeling state or events with discriminated unions for exhaustive handling

When NOT to use:

• Writing simple one-liner functions that are already clear
• Academic functional programming (monads, functors, Either/Option types)
• Point-free style where arguments are implicit
• Over-extracting trivially simple expressions into named functions
• Performance-critical hot paths where function call overhead matters

Key patterns covered:

• The two-tier pattern (orchestrator + pure functions)
• The readability test ("can you understand without simulating?")
• Named predicates, constants, and transforms
• Guard clauses: flattening nested conditionals with early returns
• Discriminated unions + exhaustive switch for type-safe control flow
• Async orchestrators with

  Promise.all

  for independent operations

• as const satisfies

  for intent-revealing configuration
• The extraction decision framework
• Utility library usage: the 80/20 rule

Detailed Resources

• examples/core.md - Two-tier pattern, guard clauses, named predicates, named constants, discriminated unions, async orchestrators
• examples/data-transforms.md - Data transformation patterns, when plain JS is enough, when utility libraries help
• reference.md - Quick-reference cheat sheet with decision tables

Philosophy

Expressive TypeScript is practical, 80/20 functional programming focused on readability. The core test for any block of code:

"Can someone understand the code's flow without simulating any of its parts?"

If the answer is no, extract the part that requires simulation into a named function or constant. If the answer is yes, leave it alone -- even if it could theoretically be "cleaner."

This is NOT:

• Monads, functors, or Either/Option types -- those belong in a different skill
• Point-free style -- implicit arguments obscure intent for most readers
• Religious functional purity -- side effects in orchestrators are fine; the pure functions underneath are what matter
• Over-extraction -- three similar lines of code is better than a premature abstraction

The two core ideas:

1. Orchestrators read like pseudocode. Guard clauses, named function calls, assembly. No inline logic that requires simulation.
2. Pure functions do one thing. Each has a name that communicates its purpose. Each is independently testable.

When to apply this skill:

• Any function longer than ~15 lines that mixes concerns
• Any expression where a reader would need to trace through logic to understand intent
• Any repeated logic pattern that lacks a descriptive name

When NOT to apply:

• A single

  .map()

  or

  .filter()

  that already reads clearly
• Functions that are already one level of abstraction
• Trivially simple code where extraction would add noise

Core Patterns

Pattern 1: The Two-Tier Pattern

Every non-trivial function follows the same structure: an orchestrator at the top that reads like pseudocode, calling pure functions at the bottom that each do one thing.

The Orchestrator (Top Tier)

// Orchestrator: reads like a step-by-step plan
function processUserImport(rawData: RawImportData): ImportResult {
  // 1. Guard clauses
  if (!rawData.users.length) {
    return { imported: 0, skipped: 0, errors: [] };
  }

  // 2. Named function calls for each step
  const validated = rawData.users.filter(isValidUser);
  const normalized = validated.map(normalizeUserRecord);
  const deduped = removeDuplicatesByEmail(normalized);
  const { existing, newUsers } = separateExistingUsers(deduped);

  // 3. Assembly
  return {
    imported: newUsers.length,
    skipped: existing.length,
    errors: rawData.users.length - validated.length,
  };
}

Why good: Each line communicates intent through its function name. A reader knows WHAT happens at each step without reading HOW any step works. Guard clauses are at the top. No inline lambdas obscure the flow.

The Pure Functions (Bottom Tier)

// Pure function: one job, named for purpose
function isValidUser(user: RawUser): boolean {
  return user.email.includes("@") && user.name.trim().length > 0;
}

function normalizeUserRecord(user: RawUser): NormalizedUser {
  return {
    email: user.email.toLowerCase().trim(),
    name: user.name.trim(),
    role: user.role ?? DEFAULT_ROLE,
  };
}

function removeDuplicatesByEmail(users: NormalizedUser[]): NormalizedUser[] {
  const seen = new Set<string>();
  return users.filter((user) => {
    if (seen.has(user.email)) return false;
    seen.add(user.email);
    return true;
  });
}

Why good: Each function does one thing, has a descriptive name, and is testable in isolation without mocks or state setup.

Full before/after examples: See examples/core.md for complete orchestrator transformations.

Pattern 2: The Readability Test

Before extracting or refactoring, apply this test to any block of code:

"Can someone understand the code's flow without mentally simulating any of its parts?"

// Fails the readability test -- requires simulation
const result = items
  .filter(
    (item) =>
      item.status === "active" &&
      item.createdAt > cutoffDate &&
      !excludedIds.has(item.id),
  )
  .map((item) => ({
    ...item,
    displayName: item.firstName + " " + item.lastName,
    age: Math.floor((Date.now() - item.birthDate.getTime()) / MS_PER_YEAR),
  }));

Why bad: A reader must mentally execute the filter predicate and the map transform to understand what this produces. The intent is buried in implementation.

// Passes the readability test -- intent is clear from names
const activeItems = items.filter(isActiveAfterCutoff);
const displayRecords = activeItems.map(toDisplayRecord);

Why good: Each step communicates intent. A reader knows the filter selects active items after a cutoff and the map creates display records -- without reading either function's body.

When the Test Says "Leave It Alone"

// Already passes -- don't over-extract
const names = users.map((user) => user.name);
const activeUsers = users.filter((user) => user.isActive);
const total = prices.reduce((sum, price) => sum + price, 0);

Why good: These are already clear single-expression operations. Extracting

getName

isActive

sumPrices

Pattern 3: Named Abstractions

When an expression requires simulation, give it a name that communicates intent.

Named Predicates

// Before: requires simulation to understand filter criteria
const lines = diff.filter(
  (line) => line.startsWith("+") && !line.startsWith("+++"),
);

// After: name communicates intent
const lines = diff.filter(isContentAddition);

function isContentAddition(line: string): boolean {
  return line.startsWith("+") && !line.startsWith("+++");
}

Why good:

isContentAddition

Named Constants

// Before: magic setup with no context
const skill = createMockSkill("react", {
  conflictsWith: ["vue", "angular"],
  requires: ["typescript"],
});

// After: name communicates purpose
const REACT_WITH_FRAMEWORK_CONFLICTS = createMockSkill("react", {
  conflictsWith: ["vue", "angular"],
  requires: ["typescript"],
});

Why good: When this constant appears in a test, the reader knows its purpose without scrolling to its definition. The name encodes the relevant characteristics.

Named Transforms

// Before: inline formatting logic obscures orchestrator flow
const message = results
  .map((r) =>
    r.success ? `  Installed ${r.name}` : `  Failed ${r.name}: ${r.error}`,
  )
  .join("\n");

// After: name communicates intent
const message = results.map(formatInstallResult).join("\n");

function formatInstallResult(result: InstallResult): string {
  if (result.success) return `  Installed ${result.name}`;
  return `  Failed ${result.name}: ${result.error}`;
}

Why good: The orchestrator reads as "format each result, join with newlines." The formatting details are available but not in the way.

More examples: See examples/core.md for before/after named abstraction patterns.

Pattern 4: The Extraction Decision Framework

Not every expression should be extracted. Use this decision tree:

Does this block require mental simulation to understand?
|-- NO -> Leave it inline. Don't over-extract.
+-- YES -> Does the same logic appear in 2+ places?
    |-- YES -> Extract to shared function (DRY + readability).
    +-- NO -> Would a named function communicate intent the expression doesn't?
        |-- YES -> Extract. The name adds value.
        +-- NO -> Leave it. Extraction would just move code without adding clarity.

Extract: Block Requires Simulation

// Before: simulation required to understand what this produces
const categories = Object.entries(skills).reduce<Record<string, Skill[]>>(
  (acc, [id, skill]) => {
    const cat = skill.category;
    if (!acc[cat]) acc[cat] = [];
    acc[cat].push(skill);
    return acc;
  },
  {},
);

// After: intent is clear from the name
const categories = groupSkillsByCategory(skills);

Don't Extract: Already Clear

// Already clear -- extracting would just move one line
const ids = skills.map((skill) => skill.id);
const hasConflicts = conflicts.length > 0;
const displayName = `${firstName} ${lastName}`;

Why good: These are trivially understandable. A function named

getIds

checkHasConflicts

buildDisplayName

Don't Extract: Name Would Be As Complex As Implementation

// Don't extract this:
const isSelected = selectedIds.has(item.id);

// Because the extraction would be:
function isItemSelected(item: Item, selectedIds: Set<string>): boolean {
  return selectedIds.has(item.id);
}
// The name doesn't communicate more than the expression itself

Pattern 5: Guard Clauses (Flatten Nested Conditionals)

Deeply nested if/else blocks force a reader to maintain a mental stack of conditions. Guard clauses invert conditions and return early, keeping the happy path un-nested.

// Flat: each guard exits early, happy path has zero nesting
function getDiscount(user: User, cart: Cart): number {
  if (!user.isActive) return 0;
  if (cart.items.length === 0) return 0;
  if (!user.membership) return STANDARD_DISCOUNT;

  return calculateMemberDiscount(user.membership, cart.total);
}

Why good: Each guard clause handles one concern and exits. The reader never needs to track which

else

Full before/after transformation: See examples/core.md for deeply nested code flattened to guard clauses.

Pattern 6: Discriminated Unions + Exhaustive Switch

When a value can be one of several states, a discriminated union with an exhaustive switch makes the type system enforce that every case is handled. Adding a new variant causes a compile error wherever handling is missing.

type TaskStatus = "pending" | "running" | "completed" | "failed";

function getStatusMessage(status: TaskStatus): string {
  switch (status) {
    case "pending":
      return "Waiting to start";
    case "running":
      return "In progress...";
    case "completed":
      return "Done";
    case "failed":
      return "Something went wrong";
    default: {
      const _exhaustive: never = status;
      return _exhaustive;
    }
  }
}

Why good: The

never

Full pattern with discriminated object unions: See examples/core.md for the complete discriminated union pattern.

Pattern 7: Async Orchestrators

The two-tier pattern applies equally to async code. Async orchestrators

await

Promise.all

async function onboardNewUser(input: OnboardInput): Promise<OnboardResult> {
  const user = await createUserRecord(input);

  // Independent operations -- run in parallel
  const [profile, settings] = await Promise.all([
    initializeProfile(user.id, input.preferences),
    applyDefaultSettings(user.id),
  ]);

  await sendWelcomeEmail(user.email, profile.displayName);

  return { user, profile, settings };
}

Why good: The orchestrator reads as a step-by-step plan. Independent operations are grouped in

Promise.all

Full before/after example: See examples/core.md for an async function decomposed from mixed-concern code.

Pattern 8:

as const satisfies

for Configuration

When defining static configuration objects,

as const satisfies Shape

typeof

keyof

interface RouteConfig {
  path: string;
  auth: boolean;
}

const ROUTES = {
  home: { path: "/", auth: false },
  dashboard: { path: "/dashboard", auth: true },
  settings: { path: "/settings", auth: true },
} as const satisfies Record<string, RouteConfig>;

// Type of ROUTES.home.path is "/", not string
// typeof ROUTES gives you the full literal structure for keyof usage

Why good: The

satisfies

as const

satisfies

{ pth: "/" }

<decision_framework>

Decision Framework

When to Apply the Two-Tier Pattern

Is this function > ~15 lines?
|-- NO -> Is it mixing multiple concerns (validate + transform + assemble)?
|   |-- YES -> Apply two-tier pattern
|   +-- NO -> Leave it. Short single-concern functions are fine as-is.
+-- YES -> Does it have clear logical steps?
    |-- YES -> Apply two-tier pattern: orchestrator calls named functions
    +-- NO -> Consider breaking into separate functions by responsibility first

When to Use a Utility Library vs Plain JS

Is this a single .map(), .filter(), or .reduce()?
|-- YES -> Use plain JS. A utility library adds dependency without clarity.
+-- NO -> Is the operation a known concept (group-by, count-by, set-difference)?
    |-- YES -> Does the utility library name match the concept?
    |   |-- YES -> Use the library. groupBy(skills, s => s.category) is
    |   |          clearer than a manual reduce.
    |   +-- NO -> Use plain JS with a named function.
    +-- NO -> Are there 3+ chained transformations?
        |-- YES -> Consider pipe() if intermediate variables would obscure flow.
        +-- NO -> Use plain JS with named intermediate variables.

The 80/20 Rule for Utility Libraries

Use utility functions when the function name IS the documentation:

groupBy(items, fn)

items.map(fn)

countBy(items, fn)

items.filter(fn)

difference(a, b)

items.find(fn)

partition(items, fn)

items.some(fn)

items.every(fn)

indexBy(items, fn)

items.reduce(fn, init)

pipe(data, ...fns)

.map().filter()

Full data transformation examples: See examples/data-transforms.md

</decision_framework>

<red_flags>

RED FLAGS

High Priority Issues:

• An orchestrator function contains inline lambdas longer than a single expression -- extract to named functions
• A function mixes guard clauses, data transformation, side effects, and return assembly without clear separation
• Variable names describe implementation (

  filteredMappedItems

  ) instead of intent (

  activeDisplayRecords

  )
• Code uses

  .reduce()

  to build a lookup object when

  groupBy

  or

  indexBy

  communicates intent directly
• Deeply nested if/else blocks (3+ levels) instead of guard clauses with early returns
• A switch on a union type is missing the

  default: never

  exhaustiveness check -- adding a new variant will silently fall through

Medium Priority Issues:

• Using a utility library for a single

  .map()

  or

  .filter()

  that already reads clearly
• Extracting trivially simple expressions into named functions (over-extraction)
• Using

  pipe()

  for one or two operations where a variable would be clearer
• Named constants that are as complex as what they replace

Common Mistakes:

• Applying point-free style (

  items.filter(isActive)

  ) when the predicate needs context that point-free obscures -- use an explicit lambda if the predicate needs closure variables
• Extracting a function that is used exactly once and whose name is just a restatement of the single line it contains
• Creating a "utils" file that becomes a dumping ground -- group extracted functions by domain, near their callers

Gotchas & Edge Cases:

• A well-named inline lambda IS a named abstraction:

  .filter((user) => user.isActive)

  is already clear because

  isActive

  is self-documenting. Don't extract this to a separate function.
• Utility library

  pipe()

  can HURT readability when the reader doesn't know the library -- consider your team's familiarity
• Guard clauses should return early, not wrap the entire function body in an

  if

  block
• When extracting pure functions, place them at the bottom of the file or in a shared module -- not interspersed with the orchestrators they serve

• as const satisfies Shape

  -- order matters.

  satisfies Shape as const

  does not work. Lock literals first, then validate shape.
• In async orchestrators, sequential

  await

  on independent operations is a hidden performance bug -- use

  Promise.all

  when steps don't depend on each other's results
• The

  never

  exhaustiveness trick requires

  noUnusedLocals

  to not flag the variable -- use

  return _exhaustive

  instead of just assigning to avoid lint warnings

</red_flags>

<critical_reminders>

CRITICAL REMINDERS

All code must follow project conventions in CLAUDE.md (kebab-case, named exports, import ordering,

import type

, named constants)

(You MUST structure every non-trivial function as a two-tier orchestrator: guard clauses at the top, named function calls in the middle, assembly at the bottom -- NO inline data transformations in orchestrators)

(You MUST extract any expression that requires mental simulation to understand into a named function or named constant)

(You MUST name functions for WHAT they do, not HOW they do it --

isContentAddition(line)

checkLineStartsWithPlusButNotTriplePlus(line)

(You MUST read the existing code before refactoring -- understand the current structure, then improve it)

(You MUST prefer plain JS methods (

.map()

.filter()

.reduce()

Failure to follow these rules will produce code that requires mental simulation to understand -- the exact opposite of expressive TypeScript.

</critical_reminders>