awslabs/agentcore-samples - Open Source PR Review Scorecard

Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.

C-Rank Grade: A (Welcoming) - 63/100

External PR Merge Rate: 55%

Response Time: -

First Timer Success: 65%

Frequently Asked Questions

Is awslabs/agentcore-samples welcoming to first-time open-source contributors?

awslabs/agentcore-samples has a recorded first-timer success rate of 64.9%. 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 awslabs/agentcore-samples 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 62.9 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 62.9 places awslabs/agentcore-samples in the A tier.

What is the external contributor pull request merge rate for awslabs/agentcore-samples?

The external contributor pull request merge rate for awslabs/agentcore-samples is 55.3%, based on public PR activity from non-core contributors.

Are there Good First Issues available in awslabs/agentcore-samples?

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

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awslabs/agentcore-samples

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Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.

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AI Maintainer Review Guidelines

Review Persona

Constructive Code Reviewer

Warmth Score
7.4/10
Patience Score
7.8/10
Nitpick Rate
33%

Balanced & professional review environment in awslabs/agentcore-samples. Maintains strict focus on technical quality and test standards.

Top PR Submission Do's

  • •Add unit tests with >80% coverage for modified code paths
  • •Run repository linter and code formatters locally before pushing
  • •Link relevant GitHub issue ID in PR description pre-flight checklist

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without referencing an existing issue
  • •Do not mix refactoring and feature logic into a single commit
  • •Do not ping maintainers repeatedly within 24 hours of opening
Response Velocity
-
No reviewer activity recorded

Average Response Latency

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

Merge Efficiency
55.3%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
64.9%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
32 core
Highly collaborative maintainer core
Diagnostic Health HUD
55.3%
Merge Gauge
64.9%
1st-Timer
Community Vibe42/100

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Active Good First Issues (5)

View on GitHub

Summary I was trying https://github.com/awslabs/agentcore-samples/tree/main/01-features/01-harness/01-advanced-examples/05-agent-skills but in oetl_logs I could see agentcore harness was unable to load skills/xlsx Details Followed the steps in the tutorial. " "command": "ls -la .agents/skills/xlsx/ 2>/dev/null && echo 'skill directory OK' || echo 'skill not found'"" command gave me skill directory ok but in logs I could see it failed to load it. 2026-05-27T19:17:28.123Z2026-05-27 19:17:27,974 WARNING [strands.vended_plugins.skills.agent_skills] [agent_skills.py:334] [trace_id=xxx span_id=xx resource.service.name=harness_SkillsDemo_xxxx.DEFAULT trace_sampled=True] - path=</home/.agents/skills/xlsx> \| skill source path does not exist, skipping   | 2026-05-27T19:17:28.124Z2026-05-27 19:17:28,124 WARNING [strands.vended_plugins.skills.agent_skills] [agent_skills.py:110] [trace_id=xxxx span_id=xxx resource.service.name=harness_SkillsDemo_xxx.DEFAULT trace_sampled=True] - no skills were l

📅 Opened May 27, 2026💬 1 comment
Quality: 30/100Contribute

Summary Briefly describe the problem or the help you need. When creating an AgentCore registry with authorizerType: CUSTOM_JWT, the Search Records tab does not appear in the AWS console. The same registry created with AWS_IAM shows both Managed Records and Search Records tabs. Details Provide more details about your issue, including steps you’ve tried and what didn’t work. - Created registry via boto3 SDK using authorizerType: "CUSTOM_JWT" with valid authorizerConfiguration (OIDC discovery URL + custom claims) - The same JWT discovery URL and tenant ID work correctly for runtime and gateway auth - Registry status shows as ACTIVE - Console only displays the "Managed Records" tab - When creating with authorizerType: "AWS_IAM", both "Managed Records" and "Search Records" tabs appear immediately Expected Behavior What outcome were you hoping for? Search Records tab should be visible in the console for registries created with CUSTOM_JWT authorizer, same as with AWS_IAM. Add

📅 Opened May 21, 2026💬 0 comments
Quality: 30/100Contribute

Summary Having trouble understanding how to deploy Microsoft Agent Framework in .NET (though it could be Python for the sake of the tutorial) onto AWS Bedrock AgentCore. Our work environment is we are a Microsoft shop for tooling and language but build on AWS. Just looking for a very simple example of a Microsoft Agent Framework (MAF) agent in .NET or Python being deployed and running within AWS Bedrock AgentCore Details Would love even a minimal working sample I could work through, understand and build on top of.

📅 Opened Apr 9, 2026💬 1 comment
Quality: 30/100Contribute

Summary Briefly describe the problem or the help you need. _Example: Trouble setting up local dev environment_ Details Provide more details about your issue, including steps you’ve tried and what didn’t work. _Example: I ran `npm install` but the build fails with error XYZ_ Expected Behavior What outcome were you hoping for? _Example: Expected server to start after running `npm start`_ Additional Context Add any other information, screenshots, logs, or references that could help.

📅 Opened Feb 19, 2026💬 0 comments
Quality: 40/100Contribute

Summary When I am trying to launch the agentcore_runtime within sagemaker studio "launch_result = agentcore_runtime.launch()", I get the below AccessDeniedException error message. Details IAM policy for SageMakerExecution Role: { "Version": "2012-10-17", "Statement": [ { "Sid": "ExistingS3Access", "Effect": "Allow", "Action": [ "s3:ListBucket", "s3:GetObject", "s3:PutObject", "s3:DeleteObject", "s3:PutLifecycleConfiguration", "s3:GetLifecycleConfiguration" ], "Resource": [ "arn:aws:s3:::SageMaker", "arn:aws:s3:::SageMaker/", "arn:aws:s3:::bedrock-agentcore-codebuild-sources-" ] }, { "Sid": "BedrockAgentCoreRuntime", "Effect": "Allow", "Action": [ "bedrock-agentcore:CreateAgentRuntime", "bedrock-agentcore:GetAgentRuntime", "bedrock-agentcore:DeleteAgentRuntime", "bedrock-agentcore:UpdateAgentRuntime" ], "Resource": "" }, { "Sid": "SageMakerIAMSetup", "Effect": "Allow", "Action": [ "iam:CreateRole", "iam:PutRolePolicy", "iam:CreatePolicy", "iam:AttachRolePolicy", "iam:GetRole", "iam:Get

📅 Opened Jan 19, 2026💬 1 comment
Quality: 30/100Contribute
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Contributor Compatibility & Review Speed Analysis for awslabs/agentcore-samples

When evaluating whether to contribute to awslabs/agentcore-samples, 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 awslabs/agentcore-samples acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 55.3% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to awslabs/agentcore-samples

01

Is awslabs/agentcore-samples welcoming to first-time open-source contributors?

awslabs/agentcore-samples has a recorded first-timer success rate of 64.9%. 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 62.9 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 62.9 places awslabs/agentcore-samples in the Welcoming tier.

04

What is the external contributor pull request merge rate for awslabs/agentcore-samples?

The external pull request merge rate is 55.3%. 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 awslabs/agentcore-samples?

Yes, awslabs/agentcore-samples 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 awslabs/agentcore-samples 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.