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Debug Local

Checked
lightdash·vlatest·testing

Quickly isolate and resolve local data pipeline errors using Lightdash's debug-local tool.

Repository

Install on your platform

This skill no longer installs under the name debug-local. SKILL.md is marked internal, so the skills CLI hides it.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-22. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

lightdash

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

    Only contacts known or declared hosts: 127.0.0.1.

    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

    127.0.0.1local

  • 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 lightdash/lightdash at e41b8a0f7f.

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

Commit
e41b8a0f7f
Manifest
.claude/skills/debug-local/SKILL.md
Scanned
1 file, 386 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

The debug-local skill allows an AI agent to execute and inspect local files. This is useful for debugging code, examining configuration files, or interacting with locally stored data that the agent needs to understand. It provides a way for agents to troubleshoot issues without relying on external APIs or services. The skill facilitates more complex reasoning by enabling direct access to local resources.

When to use it

  • Debugging Code: An agent is generating incorrect code and you need it to inspect its own source files for errors.
  • Configuration Analysis: An agent needs to understand the contents of a local configuration file to perform a task correctly.
  • Local Data Inspection: The agent requires access to data stored locally (e.g., a CSV file) to inform its decision-making process.
  • Troubleshooting Agent Behavior: When an agent is exhibiting unexpected behavior, you can use this skill to examine the files it's interacting with.

Key capabilities

  • Execute local files
  • Inspect contents of local files
  • Access and analyze locally stored data

Example prompts

  • "Can you run my_script.py and show me the output?"
  • "What is the value of api_key in my .env file?"
  • "Please read the contents of data.csv and summarize the first 5 rows."

Tips & gotchas

The agent will need appropriate permissions to access and execute files on the local system. Be mindful of security implications when granting these permissions, especially if the agent is running in a shared environment.