aws-solutions-architect
v0.1.0Solutions architect for AWS: evidence-backed Well-Architected Framework reviews across all six pillars, generative-AI and ML architectures on Bedrock and SageMaker, and correct AWS SDK usage (boto3, JS v3, Swift).
By TalkOps AILicense: Apache-2.00 GitHub starsUpdated last week
Directory evidence
- Runtimes
- Codex, Claude Code, and Agent Plugins
- Parsed components
- 10 skill or MCP entries
- Source updated
- Oct 10, 2026
- Manifest status
- Canonical path parsed
The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →
Install aws-solutions-architect for Codex and Claude Code
codex plugin marketplace add talkops-ai/devops-plugins
codex plugin marketplace upgrade talkops-devops-plugins
codex plugin add aws-solutions-architect@talkops-devops-pluginsPaste and run these commands in a terminal with Codex. They add and refresh the talkops-devops-plugins catalog, then install this plugin.
Compatibility: the page URL and API slug “aws-solutions-architect” remain stable.
- Codex:
aws-solutions-architect@agent-plugin-marketplace→aws-solutions-architect@talkops-devops-plugins
The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.
Get the source manually
git clone https://github.com/talkops-ai/devops-pluginsClone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/agent-plugins/aws-solutions-architect/.
Plugin files
├── .codex-plugin/plugin.json├── .claude-plugin/plugin.json├── plugin.json├── skills/amazon-bedrock/SKILL.md├── skills/aws-ai-ml/SKILL.md├── skills/aws-sdk-js-v3-usage/SKILL.md├── skills/aws-sdk-python-usage/SKILL.md├── skills/aws-sdk-swift-usage/SKILL.md├── skills/aws-well-architected-review/SKILL.md├── skills/signing-in-to-aws/SKILL.md└── .mcp.json
Included Skills7
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Applies when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). Also for prompt caching, quota and throttling diagnosis, cost tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. Also covers AgentCore Payments (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, paid endpoints, agent payments). NOT for custom model training, Rekognition, or Comprehend.
Selects, deploys, and customizes AI models on Amazon SageMaker. Fine-tuning (SFT, DPO, RLVR, RLAIF), model selection, dataset preparation, evaluation, deployment to SageMaker endpoints or Bedrock, inference optimization and endpoint diagnostics. Covers the full lifecycle from planning through production. Use when fine-tuning models on SageMaker, choosing/selecting which base model to customize or fine-tune from SageMaker Hub, finding a model to deploy without fine-tuning, transforming datasets for training, checking data readiness, evaluating model quality, deploying to endpoints, benchmarking or optimizing inference, setting up IAM roles and S3 buckets for training jobs, or managing a SageMaker Managed MLflow app. Also use to check endpoint health, diagnose failures, debug latency or errors, or view container logs and CloudWatch metrics. Covers Serverless Model Customization, Nova and OSS deployment paths, and PySDK v3. NOT for Ground Truth labeling, Feature Store, or general-purpose AWS infrastructure.
AWS SDK for JavaScript v3 development patterns. Use when writing JavaScript or TypeScript code that uses AWS services via @aws-sdk/* packages (aws-sdk-js-v3), or when asked about schemas, runtime validation, serialization, or code generation in the context of the JS/TS AWS SDK.
AWS SDK for Python (boto3/botocore) development patterns. You MUST use this skill when writing Python code that uses AWS services via boto3 or botocore. This includes creating service clients or resources, configuring sessions and credentials, handling errors with ClientError, using paginators and waiters, S3 file transfers and presigned URLs, DynamoDB table operations, and any boto3/botocore client configuration. Use this skill whenever Python code imports boto3 or botocore, or when the user asks about AWS operations in Python.
AWS SDK for Swift development patterns. Use when writing Swift code that uses AWS services via aws-sdk-swift package.
Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to produce evidence-backed findings with Eisenhower-prioritized remediation. Supports full reviews (every framework best practice with BP ID citations), quick reviews (question-level), pillar-scoped reviews, score-mode reviews (a maturity scorecard with per-pillar scores and filtered findings), and lens-specific reviews using lenses discovered from the live AWS documentation. Triggers on mentions of Well-Architected review, WA review, WAR, pillar assessment, architecture review across pillars, workload assessment, cloud readiness evaluation, or a Well-Architected score, grade, or scorecard request. Does not apply to single-pillar deep-dives, learning WA concepts, ADRs, or migration readiness assessments.
Gets AWS credentials for CLI/SDK access via `aws login`. Activates when a developer needs to authenticate to AWS for local development, when an AWS operation fails due to missing or expired credentials, or when someone asks about setting up AWS access. Triggers: "set up AWS", "configure AWS", "aws login", "get credentials", "authenticate", "session expired", "token expired", "no credentials", "AccessDeniedException" with no configured credentials.
MCP servers3
- command
- uvx
- args
- mcp-proxy-for-aws-cli==1.7.0 https://aws-mcp.us-east-1.api.aws/mcp --skip-auth --read-only --metadata INSTALL_SOURCE=agent-toolkit-core
- url
- https://knowledge-mcp.global.api.aws
- command
- uvx
- args
- awslabs.aws-pricing-mcp-server@latest
- env.FASTMCP_LOG_LEVEL
- ERROR
Plugin manifests3
{
"name": "aws-solutions-architect",
"version": "0.1.0",
"description": "Solutions architect for AWS: evidence-backed Well-Architected Framework reviews across all six pillars, generative-AI and ML architectures on Bedrock and SageMaker, and correct AWS SDK usage (boto3, JS v3, Swift).",
"author": {
"name": "TalkOps AI"
},
"homepage": "https://github.com/talkops-ai/devops-plugins",
"repository": "https://github.com/talkops-ai/devops-plugins",
"license": "Apache-2.0",
"keywords": [
"aws",
"architecture",
"well-architected",
"bedrock",
"sagemaker",
"boto3",
"aws-sdk"
],
"skills": "./skills/",
"mcpServers": "./mcp.json",
"hooks": "./hooks/hooks.json",
"interface": {
"displayName": "AWS Solutions Architect",
"shortDescription": "Solutions architect for AWS",
"longDescription": "Solutions architect for AWS: evidence-backed Well-Architected Framework reviews across all six pillars, generative-AI and ML architectures on Bedrock and SageMaker, and correct AWS SDK usage (boto3, JS v3, Swift).",
"developerName": "TalkOps AI",
"category": "Cloud",
"capabilities": [
"Read"
],
"websiteURL": "https://github.com/talkops-ai/devops-plugins/tree/main/plugins/agent-plugins/aws-solutions-architect",
"brandColor": "#FF9900"
}
}{
"name": "aws-solutions-architect",
"version": "0.1.0",
"description": "Solutions architect for AWS: evidence-backed Well-Architected Framework reviews across all six pillars, generative-AI and ML architectures on Bedrock and SageMaker, and correct AWS SDK usage (boto3, JS v3, Swift).",
"author": {
"name": "TalkOps AI"
},
"homepage": "https://github.com/talkops-ai/devops-plugins",
"repository": "https://github.com/talkops-ai/devops-plugins",
"license": "Apache-2.0",
"keywords": [
"aws",
"architecture",
"well-architected",
"bedrock",
"sagemaker",
"boto3",
"aws-sdk"
]
}{
"$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
"name": "aws-solutions-architect",
"version": "0.1.0",
"description": "Solutions architect for AWS: evidence-backed Well-Architected Framework reviews across all six pillars, generative-AI and ML architectures on Bedrock and SageMaker, and correct AWS SDK usage (boto3, JS v3, Swift).",
"author": {
"name": "TalkOps AI"
},
"homepage": "https://github.com/talkops-ai/devops-plugins",
"repository": "https://github.com/talkops-ai/devops-plugins",
"license": "Apache-2.0",
"keywords": [
"aws",
"architecture",
"well-architected",
"bedrock",
"sagemaker",
"boto3",
"aws-sdk"
]
}For maintainers
If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.
[aws-solutions-architect on Agent Plugins Marketplace](https://pluginsmp.com/plugins/aws-solutions-architect)