SikamikanikoBG/homelab-monitor - Open Source PR Review Scorecard

Plug-and-play homelab dashboard in one container — GPU, local-AI VRAM, Docker, systemd, host health. Built-in read-only MCP server so AI agents can explore it too.

C-Rank Grade: S (Elite) - 82/100

External PR Merge Rate: 94%

Response Time: 21h

First Timer Success: 75%

Frequently Asked Questions

Is SikamikanikoBG/homelab-monitor welcoming to first-time open-source contributors?

SikamikanikoBG/homelab-monitor has a recorded first-timer success rate of 75.0%. 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 SikamikanikoBG/homelab-monitor respond to incoming external pull requests in approximately 21.4 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 82.1 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 82.1 places SikamikanikoBG/homelab-monitor in the S tier.

What is the external contributor pull request merge rate for SikamikanikoBG/homelab-monitor?

The external contributor pull request merge rate for SikamikanikoBG/homelab-monitor is 93.5%, based on public PR activity from non-core contributors.

Are there Good First Issues available in SikamikanikoBG/homelab-monitor?

SikamikanikoBG/homelab-monitor currently has 11 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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SikamikanikoBG/homelab-monitor

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Active (30d)S•Elite(82/100)Python

Plug-and-play homelab dashboard in one container — GPU, local-AI VRAM, Docker, systemd, host health. Built-in read-only MCP server so AI agents can explore it too.

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AI Maintainer Review Guidelines

Review Persona

Welcoming Community Builder

Warmth Score
9.4/10
Patience Score
9.0/10
Nitpick Rate
35%

Highly welcoming maintainers in SikamikanikoBG/homelab-monitor. Prompt code reviews with positive guidance for new contributors.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
21 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
93.5%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
75.0%
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
93.5%
Merge Gauge
75.0%
1st-Timer
Community Vibe74/100

Embed C-Rank Badge

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

Active Good First Issues (5)

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This is one PR, not a milestone. samples_1h keeps full history and scans in 0.09 ms, and /api/data already takes a range and buckets the data. Add until alongside range, and absolute from/to in the existing range selector. Write the range into the URL hash so any chart view is a shareable permalink. Label the resolution: 10 s inside 48 h (raw cap since 002f40f), 1 h beyond. Out of scope: rewinding the Map/inspector. That would mean threading t through ~12 renderers, 8 chart builders and 101 CURRENT_HOST reads. Source: pehota's v1 re-baseline review.

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

static/dashboard.html is served uncompressed at 865,642 bytes. With gzip it's 274,047 bytes: 3.16× smaller, or −590 KB on every first load. It's about two lines of code plus a requirements.txt pin. Done when: Content-Encoding: gzip (or br) is returned for HTML/JS/JSON. SSE /api/stream is excluded, because compression buffers the stream. The snapshot tests still pass. Source: pehota's v1 re-baseline review (reviewed at 5530ad0 / v0.37.0), re-checked against next @ 5c683e3 on 2026-10-02.

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

The dashboard is a single-file, dark-mode, chart-heavy page, and accessibility got no dedicated pass. Current state in static/dashboard.html: 40 aria-label attributes vs 4 tabindex, Chart.js canvases with no text alternative, and the tab/filter controls are mouse-driven. Nothing is broken in an aggressive way — but a keyboard-only or screen-reader user has a rough ride. Suggested scope (take any section — each is independently shippable) Keyboard reachability: tab order through the sidebar tabs, range filters and card actions; visible focus styles in the dark theme. Landmarks & roles: role on the data tables, labels on icon-only buttons (the inline-SVG header icons in particular). Charts: a short text summary per chart (peak/last value) so the sparklines aren't canvas-only. Colour: the status colours (green/amber/red dots) shouldn't be the only channel — a text state is already rendered next to most of them, so verify coverage. A PR that takes one section with a short "what I c

📅 Opened Aug 29, 2026💬 0 comments
Quality: 90/100Contribute

The security model is real and partly tested — tests/test_hardening.py covers the per-host posture checks, docker-compose.readonly.yml exists for a read-only setup, the MCP server documents its read-only guardrail, and API-key auth for the API surface lives in backend/auth.py. But the documentation is scattered: one paragraph in features.md, a "Security model" section in how-it-works.md (the no-login design decision, the read-write Docker/D-Bus sockets, the "keep it behind your LAN" guidance), and nothing else. There's no dedicated page, and the nav (mkdocs.yml) has no entry for it. For a self-hosted tool that SSHes into your fleet, that's the page a newcomer looks for first. Suggested scope A website/security.md page that gathers what's already true and documented in one place, and adds what's missing: the no-login design decision and why (already in how-it-works.md), the socket/D-Bus privileges and the write-action flags that reduce them, API-key auth for the API/MCP surface, the

📅 Opened Aug 29, 2026💬 1 comment
Quality: 100/100Contribute

The GPU tab decodes nvidia-smi's throttle bitmask into human reasons and feeds the sustained-throttle alert (gpu_throttle_sustain_s, default 120 s). For AMD cards that whole path is dark: throttle_mask / throttle / throttled are only ever set on the NVIDIA path (the nvidia-smi enrichment, app.py:5916-5919). _amd_enrich_card (the amdgpu counterpart) attaches mem_util, clocks, power_limit, p-state and temp_mem from amdgpu sysfs — but no throttle signal at all. The sample repo therefore stores throttle = 0 for every AMD sample (backend/db/repos/gpu_samples.py maps throttle → throttle_mask, defaulting to 0), so the kind of SW_THERMAL_SLOWDOWN ratchet an NVIDIA card reports has no AMD equivalent here and the GPU cockpit's sustained-thermal-throttle alert cannot fire on an AMD box, even when the card is genuinely clocked down. amdgpu exposes enough to derive a "throttled" verdict without ROCm: the pp_dpm_* clock tables (already read for p-state in _amd_enrich_card), hwmon frequency vs

📅 Opened Aug 29, 2026💬 0 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for SikamikanikoBG/homelab-monitor

When evaluating whether to contribute to SikamikanikoBG/homelab-monitor, 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 SikamikanikoBG/homelab-monitor acknowledge new external contributions in approximately 21 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 93.5% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to SikamikanikoBG/homelab-monitor

01

Is SikamikanikoBG/homelab-monitor welcoming to first-time open-source contributors?

SikamikanikoBG/homelab-monitor has a recorded first-timer success rate of 75.0%. 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 ~21 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 82.1 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 82.1 places SikamikanikoBG/homelab-monitor in the Elite tier.

04

What is the external contributor pull request merge rate for SikamikanikoBG/homelab-monitor?

The external pull request merge rate is 93.5%. 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 SikamikanikoBG/homelab-monitor?

Yes, SikamikanikoBG/homelab-monitor currently has 11 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 SikamikanikoBG/homelab-monitor 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.