type-inference

A tool for creating TypeScript type definitions from runtime data, API responses, JSON examples, JavaScript code, and other untyped values. TypeScript types describe the shape and kinds of data code expects.

In plain words
What is it for?
Use it when adding types to API results, JSON configuration, database query results, JavaScript code, or libraries without type definitions.
Why use it?
It reduces the need to write data models by hand and makes untyped data easier to use safely in TypeScript.

Skill for Claude CodeCodex

Part of the typescript-pro plugin — 5 skills, 10 commands, 8 agents shipped together

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/andronics/claude-plugin-typescript-pro/type-inference
Any agent
npx skills add andronics/claude-plugin-typescript-pro --skill type-inference
Clone the repo
git clone --depth 1 https://github.com/andronics/claude-plugin-typescript-pro

Made for: Claude Code, Codex.

Or install typescript-pro, the plugin that ships this one along with the rest of its 5 skills, 10 commands, 8 agents.

Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,850 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 $0.00046 $0.01850
Opus 5 $0.00023 $0.00925
Sonnet 5 $0.00009 $0.00370
Haiku 4.5 $0.00005 $0.00185

Measured 2d ago against content hash 3a5bae772f1f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

type-inference 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.

skills/type-inference/SKILL.md · 364 lines

How it starts

The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a TypeScript Type Inference Specialist that automatically generates accurate, well-structured types from various sources.

When to Activate

Automatically activate when detecting:

  • Untyped data structures being used
  • API responses without type definitions
  • JSON data or configuration files being imported
  • JavaScript code that needs types
  • Runtime data that needs modeling
  • External libraries without @types packages
  • Database query results without types

Type Inference Strategies

1. From Runtime Data (JSON)

Analyze JSON structure and infer optimal types:

{
  "user": {
    "id": 1,
    "name": "Alice",
    "email": "[email protected]",
    "roles": ["admin", "user"],
    "profile": {
      "age": 30,
      "verified": true
    }
  }
}

Generated Types:

interface UserProfile {
  age: number;
  verified: boolean;
}

type UserRole = 'admin' | 'user'; // Infer literal unions

interface User {
  id: number;
  name: string;
  email: string;
  roles: UserRole[];
  profile: UserProfile;
}

interface ApiResponse {
  user: User;
}

2. From API Responses

Detect API calls and model their responses:

// Detected: fetch call without types
const response = await fetch('/api/users/1');
const data = await response.json();

Generate:

interface User {
  id: number;
  name: string;
  email: string;
  createdAt: string; // ISO date string
}

interface ApiError {
  error: string;
  code: number;
}

type ApiResponse<T> =
  | { success: true; data: T }
  | { success: false; error: ApiError };

async function getUser(id: number): Promise<ApiResponse<User>> {
  const response = await fetch(`/api/users/${id}`);
  const data = await response.json();
  return data;
}

3. From JavaScript Code

Infer types from usage patterns:

// Untyped JS function
function processUser(user) {
  console.log(user.name.toUpperCase());
  return {
    id: user.id,
    displayName: user.name,
    isActive: user.status === 'active'
  };
}

Read the full file on GitHub · 364 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 · 364 lines · 46 tokens per session scan A 3a5bae772f1f

Subscribe to this mod's changes

type-inference is a skill published in the GitHub repository andronics/claude-plugin-typescript-pro (4 stars, last pushed 10mo ago), licensed MIT. It adds 46 tokens to every session and 1,850 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 2026-08-31.

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