infino-ai/infino - Open Source PR Review Scorecard

Fast search engine on object storage, with full text search, vectors, and SQL, natively on Parquet.

C-Rank Grade: S (Elite) - 76/100

External PR Merge Rate: 88%

Response Time: 1d

First Timer Success: 85%

Frequently Asked Questions

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

infino-ai/infino has a recorded first-timer success rate of 84.6%. 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 infino-ai/infino respond to incoming external pull requests in approximately 24.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 75.5 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 75.5 places infino-ai/infino in the S tier.

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

The external contributor pull request merge rate for infino-ai/infino is 88.2%, based on public PR activity from non-core contributors.

Are there Good First Issues available in infino-ai/infino?

infino-ai/infino currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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infino-ai/infino

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SElite(76/100)Rust

Fast search engine on object storage, with full text search, vectors, and SQL, natively on Parquet.

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.8/10
Patience Score
8.2/10
Nitpick Rate
35%

Collaborative maintainer environment in infino-ai/infino. Reviews community pull requests with focus on project quality.

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
1 days+
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
88.2%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
84.6%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
11 core
Highly collaborative maintainer core
Diagnostic Health HUD
88.2%
Merge Gauge
84.6%
1st-Timer
Community Vibe73/100

Embed C-Rank Badge

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

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

Active Good First Issues (1)

View on GitHub

Follow-up to #466 (which adds recall_while_ingest). While investigating recall-at-scale (#436) and the in-place cell split (#450), we ended up with two ground-truth mechanisms in the vector benches, plus some avoidable cost. This tracks the cleanup. Background The vector bench grades against a full-corpus exact oracle: it prepares the entire corpus to disk (mmap — ~400 GB at 100M×1024) and brute-forces top-k, caching the oracle in a bin (corpus/grading.rs). The bin already persists the query vectors and the labels. recall_while_ingest (#466) grades against an inline running ground truth — per-query top-k min-heaps updated as each batch streams by — so the corpus is never materialized. But it doesn't persist that GT. Follow-ups Load queries + GT from the oracle bin; don't regenerate the corpus. On a reopen / read-sweep the read path has a valid cached oracle but still regenerates the ~400 GB corpus solely to rebuild the query vectors for validation (generate_realistic_queries

📅 Opened Jul 28, 2026💬 3 comments
Quality: 50/100Contribute
Looking for more Rust beginner tasks?Explore Rust GFI

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Contributor Compatibility & Review Speed Analysis for infino-ai/infino

When evaluating whether to contribute to infino-ai/infino, 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 infino-ai/infino acknowledge new external contributions in approximately 1 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 88.2% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to infino-ai/infino

01

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

infino-ai/infino has a recorded first-timer success rate of 84.6%. 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 ~1 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 75.5 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 75.5 places infino-ai/infino in the Elite tier.

04

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

The external pull request merge rate is 88.2%. 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 infino-ai/infino?

Yes, infino-ai/infino currently has 1 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 infino-ai/infino 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.