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Building With Llms

Listed
liqiongyu·vlatest·ai-ml·Apache-2.0

Constructs complex, nuanced narratives and creative content using large language models based on user prompts and specifications.

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 liqiongyu/lenny_skills_plus --skill building-with-llms -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

liqiongyu

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: refoundai.com.

    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.

    Hosts contacted

    json-schema.orgstandardsrefoundai.comundeclared

    What it found

    • skills/building-with-llms/skillpack.json:11contacts refoundai.com
      "page_url": "https://refoundai.com/lenny-skills/s/building-with-llms",
    • skills/building-with-llms/skillpack.json:12contacts refoundai.com
      "skill_md_url": "https://refoundai.com/skills/building-with-llms/SKILL.md"

  • 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 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 liqiongyu/lenny_skills_plus at df4fa3412a.

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

Commit
df4fa3412a
Manifest
skills/building-with-llms/SKILL.md
Scanned
14 files, 1,828 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 enables AI agents to construct and interact with Large Language Models (LLMs). It facilitates building custom LLM applications, allowing for tailored workflows and integrations. The skill provides tools for managing prompts, data, and configurations related to LLM interactions.

When to use it

  • Automating repetitive tasks involving LLMs, such as generating content or summarizing documents.
  • Creating specialized AI assistants with specific knowledge domains by integrating custom LLMs.
  • Developing complex workflows that require multiple LLM calls and data processing steps.
  • Building applications that leverage the reasoning and generation capabilities of LLMs in a structured way.

Key capabilities

  • LLM application construction
  • Prompt management
  • Data integration with LLMs
  • Configuration for LLM interactions

Example prompts

  • "Build an LLM application to summarize customer reviews."
  • "Create a prompt template for generating marketing copy based on product descriptions."
  • "Integrate this dataset into my LLM workflow for training purposes."

Tips & gotchas

This skill requires familiarity with Large Language Models and their underlying concepts. Effective use depends on understanding how to structure prompts and manage data for optimal results.