Agent skill · data analytics · shubhamsaboo
dependency-doctor
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.
Why this skill is useful
Adds specific checks for dependency manifest issues that the AI wouldn't reliably generate on its own.
What it needs
Requires python3 installed locally. About 3k tokens when loaded. Last updated 2026-08-03. 131,141 stars on the source repository.
What this skill does
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: The default path is fully offline. It reads only the selected manifest. The report shape is: The offline checks cover: Python standard-library names published as packages Known backports that should not be installed on supported Python versions Dependencies without a usable version constraint Repeated package entries Conflicting exact pins for the same package For package.json, Python-specific standard-library and backport checks do not apply. The doctor still checks unpinned values and repeated dependency entries. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills shubhamsaboo/dependency-doctor