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Typescript

Checked
lambdamechanic·vlatest·backend

Generates, debugs, and refactors TypeScript backend code leveraging Lambda functions and serverless architectures.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add lambdamechanic/skills --skill typescript -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

lambdamechanic

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned lambdamechanic/skills at 8c6d2fa2f6.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
8c6d2fa2f6
Manifest
typescript/SKILL.md
Scanned
1 file, 61 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill allows AI agents to understand and generate TypeScript code. It can be used to write, debug, and explain TypeScript programs, as well as translate between TypeScript and other programming languages. The agent can also assist in understanding existing TypeScript projects by providing explanations of the codebase.

When to use it

  • Code Generation: Generate new TypeScript functions or modules based on a description of their functionality.
  • Debugging Assistance: Identify and fix errors in existing TypeScript code.
  • Code Explanation: Get clear explanations of complex TypeScript code snippets.
  • Migration Support: Translate JavaScript code to TypeScript, aiding in project modernization efforts.

Key capabilities

  • TypeScript syntax understanding
  • Code generation
  • Debugging assistance
  • Code explanation
  • JavaScript-to-TypeScript translation

Example prompts

  • "Write a TypeScript function that calculates the factorial of a number."
  • "Explain this TypeScript code: interface User { name: string; age: number; }"
  • "Convert this JavaScript code to TypeScript: function add(a, b) { return a + b; }"

Tips & gotchas

The agent's performance is dependent on the clarity and specificity of your prompts. Providing context about the desired functionality or existing codebase will improve results.