Tlaloc-Es/killpy - Open Source PR Review Scorecard

🐍 CLI tool to find and delete unused Python virtual environments (.venv, poetry, conda, pipenv, uv). Reclaim disk space effortlessly — supports bulk delete, size reporting, and pycache cleanup.

C-Rank Grade: D (Risky) - 24/100

External PR Merge Rate: 75%

Response Time: 16d

First Timer Success: 50%

Frequently Asked Questions

Is Tlaloc-Es/killpy welcoming to first-time open-source contributors?

Tlaloc-Es/killpy has a recorded first-timer success rate of 50.0%. Repositories ranked D typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in Tlaloc-Es/killpy respond to incoming external pull requests in approximately 372.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 24.1 C-Rank™ score (D Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 24.1 places Tlaloc-Es/killpy in the D tier.

What is the external contributor pull request merge rate for Tlaloc-Es/killpy?

The external contributor pull request merge rate for Tlaloc-Es/killpy is 75.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in Tlaloc-Es/killpy?

Tlaloc-Es/killpy currently has 18 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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Tlaloc-Es/killpyD•Risky125
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Tlaloc-Es/killpy

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Active (30d)D•Risky(24/100)Low Sample (<20 PRs)Python

🐍 CLI tool to find and delete unused Python virtual environments (.venv, poetry, conda, pipenv, uv). Reclaim disk space effortlessly — supports bulk delete, size reporting, and pycache cleanup.

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AI Maintainer Review Guidelines

Review Persona

Active Open-Source Maintainer

Warmth Score
7.8/10
Patience Score
8.2/10
Nitpick Rate
20%

Active maintainer team in Tlaloc-Es/killpy welcoming community pull requests and bug fixes.

Top PR Submission Do's

  • •Ensure code complies with repository style conventions
  • •Keep PRs focused and well-documented

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without context
  • •Do not break existing automated test suites
Response Velocity
15 days+
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
75.0%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
50.0%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
75.0%
Merge Gauge
50.0%
1st-Timer
Community Vibe45/100

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Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for Tlaloc-Es/killpy
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/Tlaloc-Es/killpy)](https://getmerged.abhishekco.de/Tlaloc-Es/killpy?utm_source=github&utm_medium=badge)

Active Good First Issues (5)

View on GitHub

Motivation --min-size landed in #32 and works well. While reviewing it a handful of small rough edges came up that are not worth blocking a release over, but are each a self-contained improvement. They are grouped here so they can be picked off individually — any one of them is a reasonable first contribution. Where killpy/commands/_utils.py — SizeParamType, _SIZE_PATTERN, _SIZE_UNITS killpy/commands/{list,delete,stats,doctor,find}.py — the --min-size option declarations killpy/commands/stats.py — the --history early return Proposed approach Each item is independent; a PR fixing just one is welcome. stats --history accepts --min-size and ignores it. --history returns stored totals before any scan happens, so scan filters cannot apply. Today the value is parsed and validated, then dropped silently. It is currently documented as a caveat; raising a usage error when the two are combined would be more honest. Note --path behaves the same way, so whatever we decide should probab

📅 Opened Aug 18, 2026💬 0 comments
Quality: 90/100Contribute

Motivation On Windows the only install paths today are pip/pipx/uv, which assume a working Python setup. Scoop and winget reach developers before that point — but both work best with a self-contained executable. Proposed approach Two-step discussion: (1) decide whether to ship a standalone binary per release (PyInstaller or shiv, built and attached to the GitHub Release by the publish workflow); (2) if yes, add a Scoop bucket manifest and a winget manifest pointing at that artifact. Textual TUIs work in Windows Terminal, so the blocker is packaging, not runtime. Input from Windows users is especially welcome. Acceptance criteria Decision recorded on shipping a standalone Windows executable If approved: release workflow attaches the binary, and Scoop/winget manifests are published and documented

📅 Opened Aug 2, 2026💬 0 comments
Quality: 90/100Contribute

Motivation Arch users install CLI tools from the AUR by default, and an AUR package is a community-maintainable discovery surface. Proposed approach Publish a killpy PKGBUILD built from the PyPI sdist using python-build + python-installer (standard Python packaging guidelines). Dependencies map to python-click, python-rich, and python-textual. Include .SRCINFO and keep the version pinned to the latest release. Co-maintainers welcome — if you package for Arch and want to adopt it, say so here. Acceptance criteria killpy installable from the AUR (e.g. yay -S killpy) Install documented in README/docs

📅 Opened Aug 2, 2026💬 0 comments
Quality: 90/100Contribute

Motivation Conda users are exactly the audience with multi-GB envs directories, and conda install -c conda-forge killpy keeps them inside their own toolchain. A conda-forge feedstock is also a permanent, community-maintained distribution channel. Proposed approach Generate a recipe with grayskull pypi killpy and submit it to conda-forge/staged-recipes. Runtime dependencies (click, rich, textual) are already available on conda-forge, so the recipe should be mostly mechanical. After the feedstock is created, releases are bumped automatically by the conda-forge bot. Acceptance criteria Feedstock merged and conda install -c conda-forge killpy / mamba install killpy works Install documented in README/docs

📅 Opened Aug 2, 2026💬 0 comments
Quality: 90/100Contribute

Motivation brew install is the default install path for a large share of macOS and Linux developers, and a formula is a permanent discovery surface. A disk-cleanup tool is a natural fit for Homebrew's audience. Proposed approach Start with a personal tap (Tlaloc-Es/homebrew-killpy) hosting a formula built from the PyPI sdist (Python formula with virtualenv resources, e.g. generated via brew update-python-resources). Once install numbers and notability criteria are met, propose the formula to homebrew-core. Open to other approaches. Acceptance criteria brew install Tlaloc-Es/killpy/killpy works on macOS and Linux Formula updates on new releases (can be automated in the publish workflow) Install section of the README/docs lists the Homebrew path

📅 Opened Aug 2, 2026💬 0 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for Tlaloc-Es/killpy

When evaluating whether to contribute to Tlaloc-Es/killpy, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of Tlaloc-Es/killpy acknowledge new external contributions in approximately 15 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 75.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to Tlaloc-Es/killpy

01

Is Tlaloc-Es/killpy welcoming to first-time open-source contributors?

Tlaloc-Es/killpy has a recorded first-timer success rate of 50.0%. Repositories ranked Risky typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~15 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 24.1 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 24.1 places Tlaloc-Es/killpy in the Risky tier.

04

What is the external contributor pull request merge rate for Tlaloc-Es/killpy?

The external pull request merge rate is 75.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in Tlaloc-Es/killpy?

Yes, Tlaloc-Es/killpy currently has 18 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for Tlaloc-Es/killpy are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.