dataiku/kiji-proxy - Open Source PR Review Scorecard

Privacy proxy for your OpenAI requests

C-Rank Grade: D (Risky) - 27/100

External PR Merge Rate: -

Response Time: <1h

First Timer Success: -

Frequently Asked Questions

Is dataiku/kiji-proxy welcoming to first-time open-source contributors?

dataiku/kiji-proxy has a recorded first-timer success rate of 0.0%. 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 dataiku/kiji-proxy respond to incoming external pull requests in approximately 0.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 26.9 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 26.9 places dataiku/kiji-proxy in the D tier.

What is the external contributor pull request merge rate for dataiku/kiji-proxy?

The external contributor pull request merge rate for dataiku/kiji-proxy is 0.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in dataiku/kiji-proxy?

dataiku/kiji-proxy currently has 5 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.5/10
Patience Score
8.2/10
Nitpick Rate
20%

Collaborative maintainer environment in dataiku/kiji-proxy. Reviews community pull requests with focus on project quality.

What Contributors Actually Say

Discussions in dataiku/kiji-proxy 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

  • •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 hour
⚡ Fast reviewer response

Average Response Latency

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

Merge Efficiency
0.0%
Selective PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
0.0%
No first-timer merges recorded in window

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
CRITICAL BUS FACTOR
Single maintainer
No active GitHub maintainers found (may review internally on Gerrit or internal tools)
Diagnostic Health HUD
0.0%
Merge Gauge
0.0%
1st-Timer
Community Vibe30/100

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GetMerged C-Rank badge for dataiku/kiji-proxy
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Active Good First Issues (5)

View on GitHub

Summary ESLint does not cover the Node helper scripts under src/scripts/. The lint script runs eslint . from src/frontend (package.json → "lint": "cd src/frontend && npm run lint"), and the flat config's base path is src/frontend, so any file outside it is reported as "File ignored because outside of base path". As a result, scripts like src/scripts/electron-dev.js, remove-locales.js, notarize.js, and sync-manifest-version.js are never linted in CI. They currently have to be checked by hand, e.g.: node_modules/.bin/eslint --config src/frontend/eslint.config.js --no-config-lookup src/scripts/electron-dev.js Proposal Bring src/scripts/*.js into the lint path with a Node-oriented config block, and make npm run lint cover them automatically so they're checked in CI. Options to consider: A root-level flat config that includes both src/frontend and src/scripts, or A dedicated config block for src/scripts/**/*.js with Node globals and CommonJS sourceType. These scripts are CommonJS Node

📅 Opened Jun 26, 2026💬 0 comments
Quality: 80/100Contribute

src/backend/pii/masking_service.go orchestrates detection + generator lookup + mapping persistence, but lacks a dedicated masking_service_test.go. Sibling files (database.go, generators, detectors) all have tests. What to add Create src/backend/pii/masking_service_test.go covering: A string containing 2–3 PII types — each is masked, original/masked pairs are stored in the mapper Repeated identical PII — should map to the same dummy value within a session No PII in input — output equals input, no mappings stored Mixed-language / unicode input — does not panic and round-trips correctly Hints Stub the detector to return a fixed []Entity rather than running ONNX in tests. Reuse database_test.go patterns. Run go test ./src/backend/pii/.... Difficulty: good first issue, ~1–2 hours.

📅 Opened May 13, 2026💬 0 comments
Quality: 80/100Contribute

src/backend/processor/response.go is the only file in the processor package and has no response_test.go. Response post-processing (PII restoration / streaming handling) is on the hot path and worth testing in isolation. What to add Create src/backend/processor/response_test.go with table-driven tests for: Non-streaming JSON response — masked values are restored to originals Streaming/SSE response — chunks are reassembled and restored correctly Empty body / no PII — passes through unchanged Mapping miss (response contains a masked token with no entry in the map) — fallback is documented and tested Hints Mirror the style of src/backend/pii/database_test.go for table-driven tests. Construct mappings manually rather than wiring up the full detector. Run go test ./src/backend/processor/.... Difficulty: good first issue, ~1–2 hours.

📅 Opened May 13, 2026💬 0 comments
Quality: 80/100Contribute

src/backend/server/server.go (~28KB) handles HTTP request orchestration but has no server_test.go next to it. The rest of the backend (pii/, proxy/, providers/, config/) has companion test files, so the server is an outlier. What to add Create src/backend/server/server_test.go covering at least: Happy-path request handling for one provider (OpenAI is fine) Malformed JSON body — should return 400 Empty body — should return 400 Missing/invalid Authorization header pass-through Concurrent request handling (table-driven with t.Parallel()) Hints Use httptest.NewRecorder() / httptest.NewServer() — see src/backend/proxy/handler_test.go for the pattern already in use here. Stub or fake the PII detector + provider — you don't need a real ONNX model. Run with make test-all or go test ./src/backend/server/.... Difficulty: good first issue, ~1–2 hours.

📅 Opened May 13, 2026💬 0 comments
Quality: 80/100Contribute

The provider files under src/backend/providers/ all start with a bare package providers line. Go convention (and many linters such as revive/golint) want a // Package providers ... doc comment on at least one file, plus a short doc comment on each exported type/function. Files missing package or top-of-file doc comments: src/backend/providers/provider.go src/backend/providers/openai.go src/backend/providers/anthropic.go src/backend/providers/gemini.go src/backend/providers/mistral.go src/backend/providers/custom.go What to do Add a single `// Package providers ...` comment at the top of provider.go describing what the package does (LLM provider adapters: request/response shape per provider, masking integration). For each provider file, add a one-line comment above the file header (e.g. // File openai.go contains the OpenAI provider adapter.). Add short // FunctionName ... doc comments to exported types and functions that currently lack them. Hints Run make check or golangci-lint r

📅 Opened May 13, 2026💬 0 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for dataiku/kiji-proxy

When evaluating whether to contribute to dataiku/kiji-proxy, 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 dataiku/kiji-proxy acknowledge new external contributions in approximately <1 hour. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to dataiku/kiji-proxy

01

Is dataiku/kiji-proxy welcoming to first-time open-source contributors?

dataiku/kiji-proxy has a recorded first-timer success rate of 0.0%. 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 ~<1 hour. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 26.9 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 26.9 places dataiku/kiji-proxy in the Risky tier.

04

What is the external contributor pull request merge rate for dataiku/kiji-proxy?

The external pull request merge rate is 0.0%. 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 dataiku/kiji-proxy?

Yes, dataiku/kiji-proxy currently has 5 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 dataiku/kiji-proxy 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.