Agents DeploySAFE
Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS
Overview
Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS
b775267b72a5OBSERVED · 2026-10-23What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: agents-deploy description: > Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK/IAM/quota error diagnosis, version management, rollback, and canary deployments. Triggers on: "deploy my agent", "agentcore deploy", "deploy failed", "CDK error", "rollback", "canary deploy", "pin version", "redeploy", "deploy stuck". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build. allowed-tools: Read Grep Glob Bash metadata: type: skill version: "1.0.0" author: aws-agentcore requires-cli: ">=0.9.0" --- # deploy Deploy your AgentCore agent to AWS, or diagnose why a deploy failed. ## When to use - You're ready to deploy and want to validate config first - `agentcore deploy` failed with an error - You want to preview what deploy will create without actually deploying - You want to deploy to a specific target (staging, production) - You need to roll back to a previous version, pin to a specific version, or set up canary deployments ## Input `$ARGUMENTS` is optional: ``` /agents-deploy # interactive — pre-flight check or diagnose failure /agents-deploy preflight # validate config and IAM before deploying /agents-deploy diagnose # diagnose a failed deploy (paste error or read logs) /agents-deploy preview # show what deploy will create without deploying /agents-deploy rollback # roll back to a previous version ``` ## Process ### Step 0: Verify CLI version Run `agentcore --version`. This skill requires v0.9.0 or later. If the version is older, tell the developer to run `agentcore update` before proceeding. ### Step 1: Determine the situation Read `agentcore/agentcore.json` and `agentcore/aws-targets.json` if they exist. Ask (or infer from context): > "Are you: > > 1. About to deploy and want to check everything first > 2. Dealing with a failed deploy — what error did you see? > 3. Needing to roll back or pin a specific version?" If the developer needs versioning, rollback, or canary deployment, load [`references/versioning.md`](references/versioning.md) and follow its instructions. --- ## Path A: Pre-flight validation Run these checks before `agentcore deploy`: ### Check 1: Validate config files Show the developer this command to run: ```bash agentcore validate ``` This catches malformed `agentcore.json` before CDK even starts. ### Check 2: Verify region alignment The most common deploy failure is a region mismatch. Show the developer these commands to verify: ```bash # Your configured AWS region aws configure get region # The region in your deployment target cat agentcore/aws-targets.json # The account you're actually authenticated as aws sts get-caller-identity ``` The `region` in `aws-targets.json` must match your `aws configure` default region. The `account` must match the account ID from `sts get-caller-identity`. ### Check 3: Verify Bedrock model access Show the developer this command to check enabled models in their region: ```bash aws bedrock list-foundation-models --region $(aws configure get region) \ --query 'modelSummaries[?modelLifecycle.status==`ACTIVE`].modelId' \ --output table ``` Cross-region inference profile IDs use a geographic prefix (`us.`, `eu.`, `apac.`) or `global.` to control where inference runs. The CLI scaffolds `global.` by default (e.g., `global.anthropic.claude-sonnet-4-5-20250929-v1:0`), which routes to any commercial region. Geographic prefixes keep inference within that geography (e.g., `eu.` stays in EU regions). All prefixes require model access enabled in every destination region the profile covers. Check the Bedrock docs for which regions are included in each profile prefix. ### Check 4: Preview what will be deployed ```bash agentcore deploy --dry-run agentcore deploy --diff ``` `--dry-run` shows what resources will be created. `--diff` shows the CDK diff against what's currently deployed. ### Check 5: Verify IAM permissions Show the developer the permissions needed and this verification command: ```bash aws iam simulate-principal-policy \ --policy-source-arn $(aws sts get-caller-identity --query Arn --output text) \ --action-names iam:CreateRole \ --resource-arns "arn:aws:iam::*:role/*BedrockAgentCore*" ``` ### Run the deploy ```bash agentcore deploy -y # auto-confirm (alias: agentcore dp -y) agentcore deploy -y -v # verbose — shows resource-level events agentcore deploy --target staging -y # deploy to a specific target ``` **Memory provisioning note:** If your project includes memory, deploy takes 2–5 minutes longer while the memory resource becomes ACTIVE. This is normal — not an error. Check status: ```bash agentcore status --type memory ``` --- ## Path B: Diagnose a failed deploy ### Step B1: Read the error If the developer pasted an error, diagnose it directly. If not, read the deploy logs: ```bash # View recent deploy logs ls -lt agentcore/.cli/logs/ cat agentcore/.cli/logs/deploy-*.log 2>/dev/null | tail -100 ``` ### Step B2: Match to known failure patterns **IAM permission error:** ``` User: arn:aws:iam::123456789012:user/dev is not authorized to perform: iam:CreateRole ``` Fix: Attach the required IAM permissions (see Check 5 above). The deploying identity needs IAM write access scoped to `*BedrockAgentCore*` roles. **CDK bootstrap not run:** ``` This stack uses assets, so the toolkit stack must be deployed to the environment ``` Fix: ```bash npx cdk bootstrap aws://<YOUR_ACCOUNT_ID>/<REGION> ``` **ECR authorization error:** ``` no basic auth credentials Error response from daemon: Head "https://<YOUR_ACCOUNT_ID>.dkr.ecr.<REGION>.amazonaws.com/..." ``` Fix: ```bash aws ecr get-login-password --region <REGION> | \ docker login --username AWS --password-stdin <YOUR_ACCOUNT_ID>.dkr.ecr.<REGION>.amazonaws.
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
b775267b72a5full audit observations/trust-audit/skill/aws__agents-deploy.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-23 | b775267b72a5 | SAFE | B | 89 | first audit |
Questions
What does the agents-deploy — aws/agent-toolkit-for-aws skill do?
Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS
Is agents-deploy — aws/agent-toolkit-for-aws safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can agents-deploy — aws/agent-toolkit-for-aws access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (b775267b72a5), read on 2026-10-23. The repository is watched, and a new audit runs when it changes — this is the first audit.
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