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.
npx agentmods add skills/sequenzia/agent-alchemy/language-patternsnpx skills add sequenzia/agent-alchemy --skill language-patternsgit clone --depth 1 https://github.com/sequenzia/agent-alchemyWhat 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.
| Model | Per session | Once 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 |
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.
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 };
}
}
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.
- 2d ago First seen · 445 lines · 35 tokens per session scan A ec6fa8b5856e
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.
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