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Debug Generated Project

Checked
tuist·vlatest·testing

Automatically identifies and fixes common errors in Tuist-generated Swift projects during build processes.

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 tuist/agent-skills --skill debug-generated-project -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

tuist

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 tuist/agent-skills at 9a6ec783fe.

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

Commit
9a6ec783fe
Manifest
skills/debug-generated-project/SKILL.md
Scanned
1 file, 189 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

The debug-generated-project skill enables AI agents to inspect and analyze codebases created by other AI tools. It helps identify structural issues, missing dependencies, or logic errors within generated artifacts before they reach production.

When to use it

  • Validating the output of an AI coding agent that just scaffolded a new application.
  • Diagnosing runtime failures in a project built automatically without human review.
  • Auditing complex generated code for security vulnerabilities or anti-patterns.
  • Verifying that all required configuration files and dependencies were correctly instantiated.

Key capabilities

  • Parses and traverses directory structures of AI-generated projects.
  • Analyzes source code files for syntax errors and logical inconsistencies.
  • Identifies missing imports, broken links, or incomplete implementation blocks.
  • Generates a structured report highlighting specific lines causing issues.

Example prompts

  • "Analyze the generated React application in this folder and list any compilation errors you find."
  • "Review the AI-generated Python script for potential security vulnerabilities and logic gaps."
  • "Inspect the newly created project structure to ensure all necessary configuration files are present and correctly formatted."

Tips & gotchas

Ensure the AI agent has read permissions for the generated project directory before invoking this skill. The analysis is most effective when run immediately after generation while the codebase is fresh and unmodified.