code-simplifier

name	code-simplifier
description	Post-session code review and cleanup against a working tree of changes. Analyzes `git diff` to simplify, consolidate, and align changed code with the existing codebase — modernize syntax, remove unnecessary complexity, consolidate duplicated logic, catch efficiency issues. Use after a substantive working session, or when asked to clean up, simplify, reduce slop, consolidate, modernize, tighten up, or de-slop code. For `@cyanheads/mcp-ts-core` projects, includes specific transformations for tool/resource/prompt definitions, the ctx pattern, error factories, and framework idioms.
metadata	{"author":"cyanheads","version":"1.4","audience":"external","type":"workflow"}

Code Simplifier

Post-session cleanup pass. Reviews what changed, understands how it fits the existing codebase, and makes targeted improvements — modernizing syntax, removing unnecessary complexity, consolidating duplicated logic, catching efficiency issues. Prioritizes codebase cohesion over local perfection.

Core philosophy

Every change must earn its keep. A simplification that doesn't meaningfully improve clarity, correctness, or cohesion is noise. Don't refactor for refactoring's sake. Don't create new files, abstractions, or utilities unless they solve a demonstrated problem. If the existing code works and is readable, leave it alone. The goal is a cohesive codebase, not a pristine one.

Procedure

Phase 1: Identify changes

Run git status to see the shape of the working tree, then git diff HEAD for all uncommitted changes (staged and unstaged). Untracked files never appear in the diff — read new files directly. If the diff is empty and there are no untracked files, review the last commit (git diff HEAD~1 HEAD); if that is also empty, say the tree is clean and stop. Don't go hunting through the codebase for files to improve.

Phase 2: Understand the surrounding codebase

Don't review changes in isolation. Before any modifications:

1. Read the full files containing changes — not just the diff hunks. Understand imports, surrounding logic, module structure.
2. Identify the project language(s) and select the relevant transformation rules. Discard inapplicable rules.
3. Survey adjacent code — shared utilities, sibling modules, common patterns. You need to know what already exists before deciding something is missing.
4. Run the project's gate once before editing to establish a baseline. Find it in package.json scripts — devcheck if present, else check, else the separate typecheck / lint / test scripts; Python projects gate on uv run ruff check, uv run ruff format --check, and the configured type checker and test runner. In a Bun project that tests with Vitest, run bun run test — bare bun test bypasses the script and runs Bun's own runner. If the gate is already red, say so in the summary and don't attribute the failure to your changes.

Phase 3: Review

Evaluate the changes across these dimensions. Not every dimension applies to every diff — skip what's irrelevant.

Codebase cohesion

• Reuse — Search for existing utilities, helpers, and patterns that could replace newly-written code. Check utility directories, shared modules, and files adjacent to the changed ones. If a function already exists that does what the new code does, use it.
• Consolidation — Flag copy-paste-with-variation: near-duplicate code blocks that should be unified. Only unify if the shared abstraction is genuinely simpler than the duplicated code.
• Consistency — Check that new code follows the same patterns as the rest of the codebase: naming conventions, error handling style, import patterns, type annotation style. Normalize toward the better variant when the project is inconsistent.
• Stringly-typed code — Flag raw strings where constants, string-union types, or branded types already exist in the codebase.

Code quality

• Redundant state — State that duplicates existing state, cached values that could be derived.
• Unnecessary complexity — Deep nesting that could be guard clauses, premature abstractions, over-engineered solutions to simple problems.
• Dead code — Unreachable branches, unused variables, commented-out code. An export nothing imports is dead in an application or a package-internal module; on a published package's public surface it is API — leave it and note it in the summary.
• Defensive code for impossible states — Guards for cases the type system or upstream validation already prevents. Drop them.
• Type escapes — any, as casts that paper over a mismatch, non-null !, and @ts-ignore. Each is a claim the compiler couldn't check: replace with a narrowed type, a type guard, or a parse at the boundary. Keep the ones documenting a genuine type-system or third-party-types limitation, and prefer @ts-expect-error with a one-line reason over @ts-ignore.
• Swallowed errors — Empty catch {}, catch { return null }, and try blocks that log and continue. A fallback that hides a failure is worse than the crash it prevents: rethrow or let it propagate. When wrapping, preserve the chain (new Error(msg, { cause }), raise X from err).
• Comment noise — Strip comments that restate the code, commented-out code, and comments describing behavior the diff removed. Keep file headers, export JSDoc, and any comment carrying a why — a constraint, a workaround, an upstream bug reference.
• Outdated patterns — Verbose or legacy syntax where modern equivalents exist. See the transformation tables below.

Efficiency

• Redundant work — Repeated computations, duplicate file reads, duplicate network/API calls, N+1 query patterns.
• Missed concurrency — Independent async operations run sequentially that could run in parallel with Promise.all / Promise.allSettled.
• Unbounded fan-out — Promise.all / asyncio.gather over a caller-sized or otherwise unbounded array fires everything at once. Cap it with the project's existing concurrency helper or a batched loop. A fixed handful of independent calls needs no limit.
• No-op updates — State/store updates inside loops or event handlers that fire unconditionally. Add change-detection so downstream consumers aren't notified when nothing changed.
• TOCTOU — Pre-checking file/resource existence before operating on it. Operate directly and handle the error instead.
• Overly broad operations — Reading entire files when only a portion is needed, loading all items when filtering for one.

mcp-ts-core-specific

• Gate — bun run devcheck plus the test suite (bun run test) is the project gate in Phase 2 step 4 and Phase 4 step 5.
• Framework-provided utilities — Before hand-rolling, check src/utils/ and src/errors/ in the project and node_modules/@cyanheads/mcp-ts-core/ for framework exports: pagination helpers, schema builders, retry primitives, and the ATTR_* OTel attribute constants are framework-provided. Raw OTel attribute keys should be ATTR_* imports from @cyanheads/mcp-ts-core/utils.
• Error throwing patterns — Prefer framework error factories (McpError, validationError, notFound, httpErrorFromResponse) over raw throw new Error(). Tool handlers should throw — the framework catches, classifies, and instruments.
• Error codes — InvalidParams only for malformed JSON-RPC params shape. ValidationError for domain validation. NotFound for missing entities. Don't conflate them.
• Ctx usage — Use ctx.log, ctx.state, ctx.enrich — don't reach for global loggers or request-scoped storage directly. The ctx pattern carries tenant scope and OTel context.
• Zod schemas — Every tool input/output field needs .describe(). Zod 4 requires z.record(z.string(), z.string()) not z.record(z.string()). Use .optional() rather than .nullish() unless null is semantically distinct from absent.
• Tool annotations — readOnlyHint, idempotentHint, openWorldHint should reflect reality. A read-only tool with readOnlyHint: false gives clients the wrong picture.
• exactOptionalPropertyTypes boundaries — If a downstream type insists on the field being present-or-not-present (not present-as-undefined), use a mapped widening type at the boundary. The pattern is documented in the framework.
• format() ↔ structuredContent parity — Different MCP clients forward different surfaces. Tests should assert both surfaces carry equivalent data.
• Defensive code — the "impossible states" the framework already prevents include malformed params (Zod-validated before the handler runs) and unclassified errors (caught and classified after it throws). Guards for either are dead.
• Public surface — the MCP surface (every tool input/output schema advertised to clients) is public API for the "API compatibility" rule; changing one is a breaking change, not a refactor.

Phase 4: Apply transformations

1. Filter findings ruthlessly. If a finding is a false positive or not worth the churn, skip it. Don't argue with yourself about borderline cases — move on.
2. Stay in scope. Edit only files in the diff or new this session. Touch a file outside that set only when a finding requires it — importing an existing helper, deleting a private export the diff just orphaned — and only on the lines that finding names. Anything broader goes in the summary as a recommendation, not into the tree.
3. Correctness bugs are not this pass's job. A real defect doesn't get folded into a cleanup diff — name it in the summary with file and line so it can be handled as its own change.
4. Transform incrementally — one category of change at a time (modernize syntax, then reduce nesting, then consolidate).
5. Verify equivalence — all functionality, types, and public interfaces must remain unchanged. Re-run the gate from Phase 2 after transforming; a simplification that breaks the build is worse than the verbosity it removed.
6. Keep the diff minimal. Only touch lines that have a real reason to change. Don't reformat untouched code, add comments to code you didn't modify, or "improve" things that are already fine. Formatting belongs to the formatter (Biome, ruff): never hand-adjust whitespace, quotes, or import order, and never let a formatting-only hunk into the diff.
7. Never stage, commit, tag, or push. This pass ends with a dirty working tree and a summary; landing the changes is the caller's call.

When done, briefly summarize what was fixed, what was deliberately skipped, and any defects or out-of-scope recommendations — or confirm the code was already clean.

Common transformations

The tables below cover TypeScript and Python. For other languages, apply analogous principles: prefer modern idioms, reduce nesting, eliminate dead code, follow project conventions. Check the project's language floor (tsconfig target/lib, pyproject requires-python) before applying a version-gated row.

TypeScript (modern ESM, TS 5.x+)

Before	After	Why
const x: Foo = { ... } as Foo	const x = { ... } satisfies Foo	Type-checked without assertion
let resource = acquire(); try { ... } finally { release(resource) }	using resource = acquire()	Explicit resource disposal (TS 5.2+)
if (x !== null && x !== undefined)	if (x != null)	Idiomatic null/undefined check
arr.filter(x => x !== null) as T[]	arr.filter(x => x != null)	TS 5.5+ infers the type predicate — no cast; on older TS use an explicit (x): x is T predicate
export { foo } from './foo/index.js'	Direct imports at call sites	Avoid barrel re-exports inside the package; barrel exports are for public APIs only
import { readFile } from 'fs/promises'	import { readFile } from 'node:fs/promises'	node: protocol — unambiguous, lint-enforced in Biome
async function f() { const a = await x(); const b = await y(); }	const [a, b] = await Promise.all([x(), y()])	Parallel when independent
value || fallback	value ?? fallback	|| also swallows 0, '', and false — use ?? unless every falsy value really should take the fallback
obj.x !== undefined ? obj.x : fallback	obj.x ?? fallback	Nullish coalescing — equivalent only when null should take the fallback too
if (a) { if (b) { if (c) { ... } } }	Guard clauses with early returns	Reduce nesting
try { risky() } catch (e: any) { ... }	try { risky() } catch (e) { ... }	Under strict the catch binding is already unknown; narrow with a type guard before use
catch (err) { throw new Error('load failed') }	throw new Error('load failed', { cause: err })	Preserve the cause chain
[...arr].sort(cmp) / arr.slice().sort(cmp)	arr.toSorted(cmp)	Non-mutating array methods (ES2023) — also toReversed, toSpliced, with
const c = new AbortController(); setTimeout(() => c.abort(), ms)	AbortSignal.timeout(ms)	Built-in timeout signal; combine with a caller's signal via AbortSignal.any([...])
JSON.parse(JSON.stringify(x))	structuredClone(x)	Deep clone that preserves Date, Map, Set, and cycles
enum Status { A, B, C }	const Status = { A: 'A', B: 'B', C: 'C' } as const	enum, namespace, and constructor parameter properties are non-erasable syntax rejected by TS 5.8 erasableSyntaxOnly and Node type-stripping — but switching numeric values to strings changes serialized output; keep values stable if they're persisted
function f(a: string, b: string, c: string, d?: string)	function f(opts: FnOptions)	Options object when >3 params
throw new Error('Bad input') (in a tool handler)	throw validationError('Bad input', { field: 'x' })	Use framework error factories so the framework can classify and instrument
const ATTR_KEY = 'mcp.tool.name'	import { ATTR_MCP_TOOL_NAME } from '@cyanheads/mcp-ts-core/utils'	Use framework attribute constants

Python (3.12+)

Before	After	Why
Optional[str]	str | None	Modern union syntax (3.10+)
List[str], Dict[str, int]	list[str], dict[str, int]	Built-in generics (3.9+)
T = TypeVar("T") + def f(x: T) -> T	def f[T](x: T) -> T	PEP 695 generics (3.12+) — also class C[T]:
TypeAlias = Union[A, B, C]	type ABC = A | B | C	type statement (3.12+)
if isinstance(x, Foo): a = x.a; b = x.b	match x: case Foo(a=a, b=b): ...	Structural pattern matching (3.10+) where it destructures — not as a replacement for a flat equality if/elif chain
class Config: def __init__(self, a, b, c): self.a = a ...	@dataclass(slots=True) class Config: a: str; b: int; c: float	Less boilerplate, built-in eq/repr; frozen=True when instances shouldn't mutate
results = []; for item in items: results.append(transform(item))	results = [transform(item) for item in items]	Idiomatic comprehension
f = open('x'); try: ... finally: f.close()	with open('x') as f: ...	Context manager for resources
os.path.join(d, n), os.path.exists(p), open(p).read()	Path(d) / n, p.exists(), p.read_text()	pathlib over os.path string juggling
datetime.utcnow() / datetime.utcfromtimestamp(t)	datetime.now(UTC) / datetime.fromtimestamp(t, UTC)	Deprecated in 3.12 — the old calls return naive datetimes that compare wrong against aware ones
zip(a, b)	zip(a, b, strict=True)	3.10+ — silently truncating to the shorter input hides bugs
m = pattern.match(s) then if m: use(m)	if (m := pattern.match(s)): use(m)	Walrus operator where it removes a throwaway assignment
"Hello " + name + "!"	f"Hello {name}!"	f-string over concatenation
except Exception as e: pass	except SpecificError as e: log(e)	Catch specific, never bare except/pass
from module import *	from module import specific_name	Explicit imports only
Sequential await for independent I/O	async with asyncio.TaskGroup() as tg: tg.create_task(a()); tg.create_task(b())	Structured concurrency (3.11+) — cancels siblings on failure and raises an ExceptionGroup; asyncio.gather(..., return_exceptions=True) stays correct when every result is wanted regardless of failures

When NOT to simplify

Leave code alone when:

• It works and is readable. "I would have written it differently" is not a reason to change it.
• The change is cosmetic. Renaming a variable from data to result isn't worth the churn.
• Intentional verbosity for debugging. Verbose code may exist to make stack traces or logging clearer.
• Performance-critical paths. A less readable version may exist for measured performance reasons — check before simplifying.
• API compatibility. Don't change public function signatures, export shapes, or return types that callers depend on.
• Tests. Don't DRY up test code aggressively — test readability and isolation matter more than deduplication.