AWS Amazon CodeGuru Reviewer
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AI ReadinessAI-Aware (B-)61/100
Agent-ready OpenAPI document · curated by JenticDeveloper ToolsTesting Qahmac14 EndpointsREST
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For Agents
Associate repositories with Amazon CodeGuru Reviewer, trigger code reviews, list machine-generated recommendations, and capture feedback. Backed by 14 endpoints covering repository associations, code reviews, and recommendation feedback.
Use for: I need to associate a GitHub repository with CodeGuru Reviewer, Trigger a CodeGuru code review on a specific branch, List all open recommendations for the latest code review, Submit thumbs-up feedback on a CodeGuru recommendation
Not supported: Does not handle runtime profiling (use CodeGuru Profiler), source-code hosting, or pipeline orchestration - use for repository associations and automated code review recommendations only.
Jentic publishes the only available OpenAPI specification for Amazon CodeGuru Reviewer, keeping it validated and agent-ready. CodeGuru Reviewer runs automated code reviews against repositories hosted in CodeCommit, GitHub, GitHub Enterprise, Bitbucket, and S3. The API associates repositories with the service, triggers full or PR-scoped code reviews, lists recommendations, and captures developer feedback to improve future suggestions.
Install Jentic One Beta
Connect the Amazon CodeGuru Reviewer to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Amazon CodeGuru Reviewer, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famazonaws.com%2Fcodeguru-reviewer" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famazonaws.com%2Fcodeguru-reviewer" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Amazon CodeGuru Reviewer API.
Associate repositories from CodeCommit, GitHub, Bitbucket, or S3 with CodeGuru Reviewer
Trigger code reviews for full repositories or specific pull request branches
List recommendations with severity, file location, and suggested remediation text
Capture thumbs-up or thumbs-down developer feedback on individual recommendations
Tag repository associations and code review resources for ownership
Disassociate repositories when the service is no longer needed
Use Cases
Patterns agents use Amazon CodeGuru Reviewer API for, with concrete tasks.
★ Automated Pre-Merge Code Review
When a pull request is opened, CodeGuru Reviewer runs an automated review that surfaces concurrency issues, AWS best-practice violations, resource leaks, and security smells. Engineering teams call CreateCodeReview with a RepositoryAnalysis or PullRequest type, then poll DescribeCodeReview until State is Completed before fetching results with ListRecommendations. This adds an automated reviewer alongside human reviewers without operating any analysis infrastructure.
Trigger a code review of type RepositoryAnalysis on association arn:aws:codeguru-reviewer:..:assoc/abc and the main branch, then list the resulting recommendations
Recommendation Feedback Loop
Developers signal whether each CodeGuru recommendation was useful through PutRecommendationFeedback. The feedback (Reactions: ThumbsUp or ThumbsDown) tunes future reviews and is visible across the team. ListRecommendationFeedback exposes aggregate sentiment per recommendation, so an agent can detect patterns where the model consistently produces low-quality output and surface them for review.
Submit ThumbsUp feedback on recommendation ID rec-abc inside code review arn:aws:codeguru-reviewer:..:review/xyz
Repository Onboarding for Continuous Review
Platform teams onboarding a new repository call AssociateRepository with the source provider details (CodeCommit name, or GitHub/Bitbucket connection ARN). DescribeRepositoryAssociation polls until State is Associated, after which every PR opened on the repository can have a CodeGuru review triggered automatically. ListRepositoryAssociations gives a fleet-wide view of which repos are covered.
Associate a CodeCommit repository named payments-service with CodeGuru Reviewer and wait for the association State to reach Associated
AI Agent Integration via Jentic
Through Jentic, an AI agent uses CodeGuru Reviewer by searching for an intent like 'run a CodeGuru code review', loading the CreateCodeReview schema, and executing it with a repository association ARN and branch name. Jentic signs the SigV4 request server-side using IAM credentials in your Jentic One instance.
Search Jentic for 'run a CodeGuru code review', load the CreateCodeReview schema, and execute it for the supplied association ARN and a feature branch
Key Endpoints
14 endpoints — jentic publishes the only available openapi specification for amazon codeguru reviewer, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/associations
Associate a repository with CodeGuru Reviewer
GET
/associations
List repository associations
GET
/associations/{AssociationArn}
Describe a repository association
POST
/codereviews
Trigger a code review
GET
/codereviews/{CodeReviewArn}
Describe a code review
GET
/codereviews/{CodeReviewArn}/Recommendations
List recommendations from a code review
PUT
/feedback
Submit feedback on a recommendation
POST
/associations
Associate a repository with CodeGuru Reviewer
GET
/associations
List repository associations
GET
/associations/{AssociationArn}
Describe a repository association
POST
/codereviews
Trigger a code review
GET
/codereviews/{CodeReviewArn}
Describe a code review
GET
/codereviews/{CodeReviewArn}/Recommendations
List recommendations from a code review
PUT
/feedback
Submit feedback on a recommendation
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
A
Amazon CodeGuru Reviewer
- AI-Aware (B-)61/100
99
Foundational Compliance63
Developer Experience & Jentic Compatibility38
AI-Readiness & Agent Experience94
Agent Usability50
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
99
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A+Signals: 4
97%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
100%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
100%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
63
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: B-Signals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
50%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
38
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
50%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
0%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
50
Security
Trust, risk posture, and security compliance.
Grade: C-Signals: 1
50%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
100
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A+Signals: 1
100%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Amazon CodeGuru Reviewer by hand means signing every request with AWS Signature v4 HMAC and targeting the right regional host like codeguru-reviewer.{region}.amazonaws.com before you can associate a repository or start a review. Through Jentic you install once, import Amazon CodeGuru Reviewer from the API Directory, store the AWS access key and secret once, and your agent calls it.
Permission scoping
CodeGuru Reviewer puts the association and review ARN in the URL path (/associations/{AssociationArn}, /codereviews/{CodeReviewArn}), but those ARNs are minted by AWS at creation time rather than chosen by you, so the honest control is by operation. You limit the agent to the operations it needs, such as CreateCodeReview or ListRecommendations, so DisassociateRepository is not included unless you add it.
Credential isolation
Your AWS access key and secret are stored once, encrypted, by your own Jentic One instance and injected at execution time when the request is signed. They never enter the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'run a CodeGuru code review' or 'list recommendations from a code review', and Jentic returns the matching CodeGuru Reviewer operation with its input schema, so the agent calls CreateCodeReview or ListRecommendations directly.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Amazon CodeGuru Reviewer API through Jentic.
Why is there no official OpenAPI spec for Amazon CodeGuru Reviewer?
AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon CodeGuru Reviewer via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.
What authentication does the Amazon CodeGuru Reviewer API use?
CodeGuru Reviewer uses AWS Signature Version 4 (HMAC) signed requests with an IAM access key and secret. Through Jentic, those credentials live encrypted in your Jentic One instance and the SigV4 signature is computed server-side, so the agent context never holds the raw secret.
Can I trigger a code review on a specific pull request through the API?
Yes. CreateCodeReview accepts a Type with a RepositoryAnalysis sub-object that takes a RepositoryHead containing a BranchName. Once created, poll DescribeCodeReview until State equals Completed, then call ListRecommendations on the CodeReviewArn to fetch results.
How do I submit feedback on a CodeGuru recommendation?
Call PutRecommendationFeedback with the CodeReviewArn, RecommendationId, and a Reactions array containing ThumbsUp or ThumbsDown. ListRecommendationFeedback returns aggregate feedback so an agent can review sentiment across recommendations.
What are the rate limits for the Amazon CodeGuru Reviewer API?
AWS enforces per-account, per-region throttling on CodeGuru Reviewer; throttled requests return ThrottlingException. Code review creation is also rate-limited per repository. Use exponential backoff via the AWS SDKs that Jentic wraps.
How do I run a CodeGuru review through Jentic with an AI agent?
Run pip install jentic, then have the agent search for 'run a CodeGuru code review', load the CreateCodeReview schema, and execute it with the AssociationArn and branch. Poll DescribeCodeReview for completion, then ListRecommendations to fetch findings the agent can post back as PR comments.
Can I limit what my agent is allowed to do with the CodeGuru Reviewer API?
Yes. Because you run Jentic One yourself, your own rules decide which CodeGuru Reviewer operations and AWS credentials the agent may use. Since the association and review ARNs are minted by AWS at creation time rather than chosen by you, the honest control is by operation: you allow only the calls the agent needs, such as CreateCodeReview and ListRecommendations, so a destructive operation like DisassociateRepository is not available unless you add it. The AWS access key and secret are injected at signing time and never enter the agent's prompt or context.
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