DresdenGman/EPSILON-trading-simulator - Open Source PR Review Scorecard

Open-source quantitative decision lab: test market assumptions, preserve negative results, and reproduce evidence.

C-Rank Grade: A (Welcoming) - 64/100

External PR Merge Rate: 86%

Response Time: 21h

First Timer Success: 100%

Frequently Asked Questions

Is DresdenGman/EPSILON-trading-simulator welcoming to first-time open-source contributors?

DresdenGman/EPSILON-trading-simulator has a recorded first-timer success rate of 100.0%. Repositories ranked A 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 DresdenGman/EPSILON-trading-simulator respond to incoming external pull requests in approximately 20.9 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 64.2 C-Rank™ score (A 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 64.2 places DresdenGman/EPSILON-trading-simulator in the A tier.

What is the external contributor pull request merge rate for DresdenGman/EPSILON-trading-simulator?

The external contributor pull request merge rate for DresdenGman/EPSILON-trading-simulator is 85.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in DresdenGman/EPSILON-trading-simulator?

DresdenGman/EPSILON-trading-simulator currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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DresdenGman/EPSILON-trading-simulator

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Active (30d)A•Welcoming(64/100)Low Sample (<20 PRs)TypeScript

Open-source quantitative decision lab: test market assumptions, preserve negative results, and reproduce evidence.

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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 DresdenGman/EPSILON-trading-simulator 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
20 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
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
85.7%
Merge Gauge
100.0%
1st-Timer
Community Vibe79/100

Embed C-Rank Badge

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

GetMerged C-Rank badge for DresdenGman/EPSILON-trading-simulator
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Active Good First Issues (3)

View on GitHub

The status page correctly discloses that historical universes are user-selected and that EPSILON does not yet provide a point-in-time constituent database. Survivorship bias therefore remains possible. A public design discussion would make this limitation actionable and give quantitative-finance contributors a concrete research problem to help solve. Suggested scope: define how universe membership is associated with an effective date; cover delistings, symbol changes, mergers, suspensions, and missing observations; add universe provenance to exported evidence artifacts; define behavior when historical membership cannot be established; create a small public fixture with a known membership change; add a test showing that a security unavailable at the decision date is not silently included; keep present-day ticker lists explicitly labeled when they are used. A design document and fixture are sufficient for the first contribution; a complete commercial constituent database is not require

📅 Opened Sep 7, 2026💬 0 comments
Quality: 90/100Contribute

The instrument rate limiter currently stores counters in an in-memory map attached to globalThis and identifies a client using cf-connecting-ip, falling back to the shared key anonymous. That is useful as a local guard, but edge instances do not necessarily share memory. Counters can therefore differ between instances or reset with the runtime. In environments without the Cloudflare header, unrelated users may also share the same bucket. Suggested scope: document the threat and abuse model for the historical-data and impact endpoints; define a privacy-preserving client-key policy for production and local development; use a shared or platform-backed limiter where enforcement must be consistent; specify fail-open or fail-closed behavior when the backing store is unavailable; add tests for missing headers, window rollover, concurrent requests, and multiple runtime instances; continue avoiding storage of unnecessary personal data. This issue is about predictable resource protection; it i

📅 Opened Sep 7, 2026💬 0 comments
Quality: 90/100Contribute

The repository currently describes two different canonical product paths. The root README presents instrument/ and the public /lab workflow as the current product, while docs/PRODUCT_ARCHITECTURE.md describes /landing → /dashboard → /dashboard/backtest and docs/REPRODUCIBILITY.md still asks readers to run website/ and open /demo. This makes it difficult for a new contributor to know which workflow should be reproduced or changed. Suggested scope: identify the current canonical application and reproduction path in one source of truth; mark historical product documents clearly as legacy, or update them to the current instrument; add a short documentation index that separates current and historical material; verify all published commands from a clean clone; preserve the historical record without presenting retired routes as the active workflow. Done when a first-time contributor can determine the supported runtime, route, and verification command without comparing several conflictin

📅 Opened Sep 7, 2026💬 0 comments
Quality: 100/100Contribute
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Contributor Compatibility & Review Speed Analysis for DresdenGman/EPSILON-trading-simulator

When evaluating whether to contribute to DresdenGman/EPSILON-trading-simulator, 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 DresdenGman/EPSILON-trading-simulator acknowledge new external contributions in approximately 20 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 DresdenGman/EPSILON-trading-simulator

01

Is DresdenGman/EPSILON-trading-simulator welcoming to first-time open-source contributors?

DresdenGman/EPSILON-trading-simulator has a recorded first-timer success rate of 100.0%. Repositories ranked Welcoming 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 ~20 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 64.2 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 64.2 places DresdenGman/EPSILON-trading-simulator in the Welcoming tier.

04

What is the external contributor pull request merge rate for DresdenGman/EPSILON-trading-simulator?

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 DresdenGman/EPSILON-trading-simulator?

Yes, DresdenGman/EPSILON-trading-simulator currently has 2 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 DresdenGman/EPSILON-trading-simulator 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.