mkbhardwas12/prismos-ai - Open Source PR Review Scorecard

Local-first desktop AI: chat with your files, turn one line into a living 3D scene, investigate logs and harden configs. Runs on your laptop, works offline.

C-Rank Grade: S (Elite) - 75/100

External PR Merge Rate: 86%

Response Time: 5h

First Timer Success: 100%

Frequently Asked Questions

Is mkbhardwas12/prismos-ai welcoming to first-time open-source contributors?

mkbhardwas12/prismos-ai has a recorded first-timer success rate of 100.0%. Repositories ranked S 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 mkbhardwas12/prismos-ai respond to incoming external pull requests in approximately 5.5 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 74.8 C-Rank™ score (S 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 74.8 places mkbhardwas12/prismos-ai in the S tier.

What is the external contributor pull request merge rate for mkbhardwas12/prismos-ai?

The external contributor pull request merge rate for mkbhardwas12/prismos-ai is 85.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in mkbhardwas12/prismos-ai?

mkbhardwas12/prismos-ai currently has 8 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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mkbhardwas12/prismos-aiS•Elite378
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mkbhardwas12/prismos-ai

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InactiveS•Elite(75/100)Low Sample (<20 PRs)Rust

Local-first desktop AI: chat with your files, turn one line into a living 3D scene, investigate logs and harden configs. Runs on your laptop, works offline.

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AI Maintainer Review Guidelines

Review Persona

Strict Architecture Gatekeeper

Warmth Score
6.9/10
Patience Score
7.8/10
Nitpick Rate
30%

Strict review standards in mkbhardwas12/prismos-ai. Ensure PR scope matches issue requirements closely before requesting review.

What Contributors Actually Say

Discussions in mkbhardwas12/prismos-ai focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.

Hidden Friction Signals

Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.

Unwritten Rules

  • •1) Keep PR scope strictly aligned with the linked issue.
  • •2) Ensure local linters pass before opening a review.
  • •3) Maintain full test coverage for modified logic.

Top PR Submission Do's

  • •Add or update tests for changed behavior before requesting review
  • •Update docs or README when behavior changes
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not leave requested test coverage unresolved
  • •Do not ship user-facing changes without matching docs
  • •Do not mix unrelated refactors in a single PR
Response Velocity
5 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
85.7%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
100.0%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
5 core
Small core review team
Diagnostic Health HUD
85.7%
Merge Gauge
100.0%
1st-Timer
Community Vibe90/100

Embed C-Rank Badge

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

GetMerged C-Rank badge for mkbhardwas12/prismos-ai
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Active Good First Issues (5)

View on GitHub

Every cargo build / cargo clippy prints: warning: the following packages contain code that will be rejected by a future version of Rust: imap-proto v0.10.2 note: to see what the problems were, use the option `--future-incompat-report`, or run `cargo report future-incompatibilities --id 1` imap-proto is a transitive dependency of imap = "2.4" (src-tauri/Cargo.toml line 68), used only by the optional, off-by-default Email Keeper agent. Task Run cargo report future-incompatibilities in src-tauri/ and paste the relevant lint in the PR. Check whether a newer imap release (3.x is in RC) pulls a fixed imap-proto; if so bump and adapt email_keeper.rs to any API changes. If not, open an upstream issue and link it here — that is still a useful outcome. cargo test must stay green; Email Keeper has no live-server tests, so please also do a manual sanity check that the crate still compiles with the feature paths used in email_keeper.rs. No network egress may be introduced — this is a depende

📅 Opened Sep 20, 2026💬 4 comments
Quality: 100/100Contribute

Windows is a shipped platform (.msi / .exe on every release) but CI only runs cargo test on ubuntu-latest (.github/workflows/ci.yml, three jobs all runs-on: ubuntu-latest). That is how the two Windows-only failures in #29 went unnoticed. Task Add a second Backend (Rust) leg on windows-latest that runs cargo test in src-tauri/ (a matrix on the existing job is fine). It is expected to be red at first because of #29 — that is the point. Mark it continue-on-error: true until #29 is fixed, then flip it to blocking in the same PR that fixes #29 or a follow-up. Keep the Linux leg unchanged; don't add clippy/coverage to the Windows leg yet. Good to know Tauri's Windows prerequisites for a test run are lighter than for a build; cargo test does not need WebView2 installed. If a crate needs a system dep, note it in the PR. Cache ~/.cargo and src-tauri/target the same way the Linux job does so the leg stays under ~10 min. If you want to take this, comment here and I'll assign it. Happy to re

📅 Opened Sep 20, 2026💬 0 comments
Quality: 90/100Contribute

Reported by @EthemKD in #28 while validating on Windows — not caused by that PR; they reproduce on the unchanged base aed6dba. CI only runs Ubuntu, so these are invisible to the badge even though Windows is a shipped platform. Failing on Windows (cargo test, 405 passed / 2 failed): app_builder::tests::injects_offline_csp_into_html_only project_reviewer::tests::scan_rejects_home_and_missing Both pass on Linux (CI) and macOS (407/407 locally). Likely suspects are platform assumptions in the tests — path separators / line endings for the CSP one, and home-directory resolution (HOME vs USERPROFILE) for the reviewer one — but that's unconfirmed. Needs: the actual assertion output from a Windows run, then a fix in either the test or the code. Worth considering a windows-latest leg for cargo test in CI afterwards so this can't regress silently.

📅 Opened Sep 20, 2026💬 2 comments
Quality: 90/100Contribute

Everything needed for an AUR prismos-ai-bin package is below — the remaining work is creating an AUR account, git clone ssh://[email protected]/prismos-ai-bin.git, adding these files, and pushing (run makepkg --printsrcinfo > .SRCINFO first). PKGBUILD # Maintainer: your name <your@email> pkgname=prismos-ai-bin pkgver=0.6.0 pkgrel=1 pkgdesc="Ask a local Ollama model about your own files, offline (AppImage)" arch=('x86_64') url="https://github.com/mkbhardwas12/prismos-ai" license=('MIT') depends=('fuse2' 'zlib') optdepends=('ollama: local model runtime (required at runtime)') options=(!strip) _appimage="PrismOS-AI_${pkgver}_amd64.AppImage" source=("${_appimage}::${url}/releases/download/v${pkgver}/${_appimage}" "${url}/raw/main/LICENSE") sha256sums=('9852acbf09e977f77842727e62781ff54397468865c80a0282c92df05bdad892' 'SKIP') prepare() { chmod +x "${_appimage}" ./"${_appimage}" --appimage-extract >/dev/null } package() { install -Dm755 "${_appimage}"

📅 Opened Aug 14, 2026💬 6 comments
Quality: 90/100Contribute

Everything needed to put PrismOS-AI on winget is below — the remaining work is forking microsoft/winget-pkgs, adding these three files under manifests/m/MkBhardwas/PrismOS-AI/0.6.0/, and opening the PR (their validation bots do the rest). MkBhardwas.PrismOS-AI.yaml PackageIdentifier: MkBhardwas.PrismOS-AI PackageVersion: 0.6.0 DefaultLocale: en-US ManifestType: version ManifestVersion: 1.6.0 MkBhardwas.PrismOS-AI.installer.yaml PackageIdentifier: MkBhardwas.PrismOS-AI PackageVersion: 0.6.0 InstallerLocale: en-US Platform: - Windows.Desktop MinimumOSVersion: 10.0.17763.0 InstallerType: wix Scope: user InstallModes: - interactive - silent - silentWithProgress UpgradeBehavior: install Installers: - Architecture: x64 InstallerUrl: https://github.com/mkbhardwas12/prismos-ai/releases/download/v0.6.0/PrismOS-AI_0.6.0_x64_en-US.msi InstallerSha256: 6443316EB011AA91BC9852FB1B38580E16CE10FDAB98F06901413956CD5EB27C ManifestType: installer ManifestVersion: 1.6.0 MkBhardwas.PrismOS-AI.locale.

📅 Opened Aug 14, 2026💬 4 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for mkbhardwas12/prismos-ai

When evaluating whether to contribute to mkbhardwas12/prismos-ai, 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 mkbhardwas12/prismos-ai acknowledge new external contributions in approximately 5 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 85.7% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to mkbhardwas12/prismos-ai

01

Is mkbhardwas12/prismos-ai welcoming to first-time open-source contributors?

mkbhardwas12/prismos-ai has a recorded first-timer success rate of 100.0%. Repositories ranked Elite 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 ~5 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 74.8 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 74.8 places mkbhardwas12/prismos-ai in the Elite tier.

04

What is the external contributor pull request merge rate for mkbhardwas12/prismos-ai?

The external pull request merge rate is 85.7%. 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 mkbhardwas12/prismos-ai?

Yes, mkbhardwas12/prismos-ai currently has 8 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 mkbhardwas12/prismos-ai 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.