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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.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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name dependency-doctor description 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. license Apache-2.0 compatibility Python 3.11+. Offline by default. Network access to pypi.org occurs only when the user explicitly approves --online. metadata {"author":"Matt Van Horn","version":"1.0.0","source":"https://github.com/Shubhamsaboo/awesome-llm-apps"} 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: { "file" : "/path/to/requirements.txt" , "findings" : [ { "severity" : "high" , "kind" : "stdlib-shadowing" , "package" : "pathlib" , "line" : 4 , "why" : "..." , "fix" : "..." } ] , "summary" : { "total" : 1 , "by_severity" : { "high" : 1 } , "by_kind" : { "stdlib-shadowing" : 1 } , "online" : false } } 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. Explain the diagnosis Read references/dependency-pitfalls.md before presenting findings. Lead with high severity items, then medium and low. For each finding, include: Package and source line What can break The suggested fix Do not call every range a conflict. The deterministic core reports conflicting constraints only when exact pins disagree. Compatible constraints split across multiple lines are duplicate entries that should be combined. If there are no findings, say what was checked and note the limits. A clean report is not a CVE audit or a full dependency resolver. Optional PyPI yank check The online check sends package names and exact pinned versions to pypi.org . Ask for permission before enabling it, even if the user previously requested an offline diagnosis. python3 scripts/dep_doctor.py /path/to/requirements.txt --json --online It reports an exact Python release only when every file for that release is marked yanked. Network failures become low-severity findings instead of hiding the offline diagnosis. Offer fixes, do not apply them silently After explaining the report, offer a focused edit. Wait for approval before changing the manifest. Remove standard-library packages from supported Python projects Remove obsolete backports, or add a Python-version marker when an old runtime genuinely needs one For an unpinned dependency, inspect the working environment's installed version, confirm it is intended, and propose an exact reviewed pin Keep one entry for duplicates and combine compatible constraints For conflicting exact pins, inspect dependents before choosing a version Replace a yanked pin with a tested, non-yanked release After any approved edit, rerun the offline diagnosis and the project's existing install or test command. Do not introduce a new CI gate. Files scripts/dep_doctor.py : stdlib-only manifest parser and diagnosis engine references/dependency-pitfalls.md : reasoning guide for the reported risks
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