ai-driven-dev/framework - Open Source PR Review Scorecard

Marketplace Framework AI-Driven Dev : Context Engineering, Plugins, Agents, Skills, Hooks, Templates, SDLC

C-Rank Grade: A (Welcoming) - 66/100

External PR Merge Rate: 54%

Response Time: -

First Timer Success: 100%

Frequently Asked Questions

Is ai-driven-dev/framework welcoming to first-time open-source contributors?

ai-driven-dev/framework 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 ai-driven-dev/framework respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 65.7 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 65.7 places ai-driven-dev/framework in the A tier.

What is the external contributor pull request merge rate for ai-driven-dev/framework?

The external contributor pull request merge rate for ai-driven-dev/framework is 53.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in ai-driven-dev/framework?

ai-driven-dev/framework does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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ai-driven-dev/framework

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Active (30d)A•Welcoming(66/100)TypeScript

Marketplace Framework AI-Driven Dev : Context Engineering, Plugins, Agents, Skills, Hooks, Templates, SDLC

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AI Maintainer Review Guidelines

Review Persona

Strict Architecture Gatekeeper

Warmth Score
7.4/10
Patience Score
8.0/10
Nitpick Rate
35%

Strict review standards in ai-driven-dev/framework. Ensure PR scope matches issue requirements closely before requesting review.

What Contributors Actually Say

Discussions in ai-driven-dev/framework 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

  • •Update docs or README when behavior changes
  • •Run the repository formatter and linter locally
  • •Link the issue and include reproduction context in the PR

Top PR Friction Pitfalls (Don'ts)

  • •Do not ship user-facing changes without matching docs
  • •Do not submit formatting-only noise with feature changes
  • •Do not open context-free PRs
Response Velocity
-
No reviewer activity recorded

Average Response Latency

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

Merge Efficiency
53.7%
Moderate PR acceptance rate

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
11 core
Highly collaborative maintainer core
Diagnostic Health HUD
53.7%
Merge Gauge
100.0%
1st-Timer
Community Vibe51/100

Embed C-Rank Badge

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Active Good First Issues (2)

View on GitHub

Description 04-spec's spec-template.md has no place for unresolved open questions (unlike prd-template.md, which has ## Open Questions). build/refine mark genuine gaps as TBD: <precise question> per references/tbd-marker.md, but with nowhere designated to put them, placement is left to the drafting agent's judgment each run — confirmed non-deterministic by two real runs on the same project: one run put 3 TBDs in ## Hard constraints (where they read as nonsense — a hard constraint can't be undecided, and it contradicts spec-validator.yml's own definition of that section: "concrete and testable, not vague"), a later run on a refined version of the same feature put the same kind of TBDs under ## Context instead. Expected behaviour spec-template.md gets a ## Open Questions section (mirroring prd-template.md). Every TBD: — regardless of which section it would eventually fill — lists there, once, deterministically. Target, Hard constraints, Non-goals, and Done-when stay 100% resolved

📅 Opened Aug 13, 2026💬 0 comments
Quality: 50/100Contribute

Problem Zed is not in the compatibility table, so a Zed user has no reason to think the framework works for them. It does: Zed reads the same context files as the tools already listed. CLAUDE.md — auto-included in every Agent Panel interaction. AGENTS.md — project-level instructions. GEMINI.md — recognised natively. AIDD writes its rules to CLAUDE.md and AGENTS.md, so Zed works out of the box today. Zed also loads Skills from ~/.agents/skills/ (global) or <worktree>/.agents/skills/ (project), following the Agent Skills specification. Scope Add a Zed row to the compatibility table. Add its install steps alongside the other tools. Acceptance criteria Zed appears in the compatibility table with its install path. The claim is verified, not assumed: install into a real Zed workspace and confirm the skills load.

📅 Opened Jun 18, 2026💬 0 comments
Quality: 40/100Contribute
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Contributor Compatibility & Review Speed Analysis for ai-driven-dev/framework

When evaluating whether to contribute to ai-driven-dev/framework, 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 ai-driven-dev/framework acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 53.7% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to ai-driven-dev/framework

01

Is ai-driven-dev/framework welcoming to first-time open-source contributors?

ai-driven-dev/framework 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 ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 65.7 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 65.7 places ai-driven-dev/framework in the Welcoming tier.

04

What is the external contributor pull request merge rate for ai-driven-dev/framework?

The external pull request merge rate is 53.7%. 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 ai-driven-dev/framework?

ai-driven-dev/framework does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for ai-driven-dev/framework 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.