language-patterns

A reference for common coding patterns in TypeScript, Python, and React. It covers choices such as strict types, safe handling of external data, and null values.

In plain words
What is it for?
Implementing typed functions, handling unknown input, defining result variants, and writing code that follows language-specific practices.
Why use it?
It helps avoid unclear, unsafe, or inconsistent code when adding features in these languages and frameworks.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/sequenzia/agent-alchemy/language-patterns
Any agent
npx skills add sequenzia/agent-alchemy --skill language-patterns
Clone the repo
git clone --depth 1 https://github.com/sequenzia/agent-alchemy

Made for: Claude Code, Codex.

Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,177 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.02177
Opus 5 $0.00017 $0.01089
Sonnet 5 $0.00007 $0.00435
Haiku 4.5 $0.00003 $0.00218

Measured 2d ago against content hash ec6fa8b5856e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

language-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

claude/core-tools/skills/language-patterns/SKILL.md · 445 lines

How it starts

The opening of the file, as written. The whole thing — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Language Patterns

This skill provides language-specific patterns and best practices. Apply patterns that match the project's language and framework.


TypeScript Patterns

Type Safety

Use strict types over any:

// Bad
function process(data: any): any {
  return data.value;
}

// Good
interface DataItem {
  value: string;
  count: number;
}

function process(data: DataItem): string {
  return data.value;
}

Use discriminated unions for variants:

type Result<T> =
  | { success: true; data: T }
  | { success: false; error: Error };

function handleResult<T>(result: Result<T>) {
  if (result.success) {
    // TypeScript knows result.data exists
    console.log(result.data);
  } else {
    // TypeScript knows result.error exists
    console.error(result.error);
  }
}

Use unknown over any for external data:

async function fetchData(): Promise<unknown> {
  const response = await fetch('/api/data');
  return response.json();
}

// Then validate/parse
const data = await fetchData();
if (isValidData(data)) {
  // Now safely typed
}

Null Handling

Use optional chaining and nullish coalescing:

// Optional chaining
const userName = user?.profile?.name;

// Nullish coalescing (only for null/undefined)
const displayName = userName ?? 'Anonymous';

// Combine them
const city = user?.address?.city ?? 'Unknown';

Use type guards:

function isUser(obj: unknown): obj is User {
  return (
    typeof obj === 'object' &&
    obj !== null &&
    'id' in obj &&
    'email' in obj
  );
}

Async Patterns

Prefer async/await over raw promises:

// Good
async function fetchUser(id: string): Promise<User> {
  const response = await fetch(`/api/users/${id}`);
  if (!response.ok) {
    throw new Error(`Failed to fetch user: ${response.status}`);
  }
  return response.json();
}

Handle errors properly:

async function safeOperation(): Promise<Result<Data>> {
  try {
    const data = await riskyOperation();
    return { success: true, data };
  } catch (error) {
    return { success: false, error: error as Error };
  }
}

Read the full file on GitHub · 445 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 445 lines · 35 tokens per session scan A ec6fa8b5856e

Subscribe to this mod's changes

language-patterns is a skill published in the GitHub repository sequenzia/agent-alchemy (43 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 2,177 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

rulesync

Generates and syncs AI rule configuration files (.cursorrules, CLAUDE.md, copilot-instructions.md) across 20+ coding tools from a single source. Use when syncing AI rules, running rulesync commands, importing or generating rule files, or managing shared AI coding configurations.

dyoshikawa/rulesync · 64 tokens

establishing-project-context

Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.

GanyuanRan/Aegis · 45 tokens

autoprompt

Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.

Spielewoy/autoprompt-skill · 56 tokens

memstack-business-gdpr

Use this skill when the user says 'GDPR', 'data protection', 'privacy compliance', 'DPA', 'DSAR', 'data subject request', 'cookie consent', 'privacy audit', 'CCPA', or asks 'do I need GDPR for this repo'. Scans the repository to detect what personal data is collected, classifies sensitivity, determines whether GDPR…

cwinvestments/memstack · 121 tokens

echo

Use when the user references past sessions, asks 'what did we do', 'do you remember', 'last session', 'recall', or 'continue from'.

cwinvestments/memstack · 35 tokens

backend-builder

Используй только внутри активного Codex Project Autopilot-проекта по утверждённому плану; не включай для обычных backend-задач вне автопилота.

hashgraph-online/awesome-codex-plugins · 43 tokens