Skills

Dependency Doctor

Check manifests for shadowed stdlib names, abandoned backports and unpinned packages.

Install

npx skills add Shubhamsaboo/awesome-llm-apps --skill dependency-doctor -g -a claude-code -y
Category
DevOps
Updated
13d ago
License
Apache-2.0
Context cost
Lightabout 1,122 tokens
Runs scripts
Yes, review before use

What it does

Checks requirements.txt, pyproject.toml, and package.json dependency manifests for surface-level direct-dependency footguns: standard-library shadowing pins, abandoned backports, unpinned dependencies, and obvious intra-manifest conflicts, plus opt-in PyPI yanked releases. Use when the user asks to check a manifest for dependency problems, asks why dependencies won't install or whether anything is wrong with their dependencies, wants a dependency autopsy, or suspects dependency manifest rot. Runs offline by default as a local tool for the user's own project, not repository CI.

Dependency Doctor

Inspect one dependency manifest on the user's machine for direct, surface-level footguns. Explain each finding in plain language, then offer a small, reviewable fix. This does not diagnose a failed pip or uv resolution.

This is a local developer tool for a project the user chooses. It is not a repository-wide lint rule, a CI gate, or a proposal to enforce dependency policy across unrelated apps.

When to use

  • The user asks to check, audit, diagnose, or autopsy a dependency manifest
  • The user wants to rule out direct-manifest issues before deeper install debugging
  • The user suspects stale pins, backports, duplicate entries, or dependency rot
  • The user asks whether anything looks wrong with their dependencies

When not to use

  • Installing the current dependencies without diagnosing them
  • Upgrading every package or adding a new package
  • A full vulnerability audit. Use pip-audit, npm audit, or the project's approved security scanner for CVE coverage
  • Creating a repo-wide CI check. This skill is user-invoked and local

Choose the manifest

Use the path the user names. If no path is given and several manifests exist, ask which one to inspect. Do not sweep the repository or edit anything merely because the skill was triggered.

Supported inputs:

  • requirements.txt
  • pyproject.toml using PEP 621 or common Poetry dependency tables
  • package.json dependency sections

Run the offline diagnosis

From this skill directory:

python3 scripts/dep_doctor.py /path/to/requirements.txt --json

The default path is fully offline. It reads only the selected manifest. The report shape is:

Read the whole SKILL.md on GitHub

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