Aws agentcore
Skill Raishin/vanguard-frontier-agentic/skills/aws/aws-agentcore
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Build, test, migrate, integrate, and deploy Amazon Bedrock AgentCore agents. Use for AgentCore runtime, local development, import/migration, deployment, Memory, Gateway/MCP tools, Identity, Observability, Browser, Code Interpreter, Evaluations, Registry, Payments, policy, and harness-vs-code-path decisions. Load references only when that component is needed.
SKILL.md
3.8 KB, 652 tokens by cl100k_base, as published. Nobody here has run it
AWS AgentCore
Purpose
Build and operate Amazon Bedrock AgentCore agents without stuffing runtime, harness, Memory, Gateway, Identity, Observability, Browser, Code Interpreter, Evaluations, Registry, Payments, policy, and environment/skills details into every prompt.
When to use
Use this skill when the user asks to:
- create or adapt an AgentCore project,
- configure local development, invocation, packaging, deployment, runtime settings, harness settings, or environment/skills paths,
- integrate AgentCore Memory, Gateway, MCP tools, Identity, Observability, Browser, Code Interpreter, Evaluations, Registry, or Payments,
- review AgentCore security, least privilege, policy, tool exposure, credential handling, migration, or production readiness.
Lean operating rules
- First decide whether the user has an existing agent or needs a new project. Do not scaffold over an existing codebase.
- For new projects, prefer the npm AgentCore CLI package
@aws/agentcorebecause current AWS documentation recommends it. - Treat the Python starter toolkit as legacy/migration-oriented unless the user is explicitly working inside an existing Python-based toolkit workflow.
- Separate code-based agents from config-based harnesses. Do not mix their guidance casually; current AWS docs describe the harness path as preview.
- Prefer current AWS documentation tools for AgentCore service behavior. Use the component facts and sampled live evidence in
references/official-sources.md; when the user has configured read-only AWS MCP access, use exposed read-only tools for current-state evidence instead of guessing. - Treat CLI syntax as version-sensitive; verify exact commands with installed tooling before production use.
- Treat Gateway policy, identity propagation, skill-path and filesystem loading, observability prerequisites, evaluation loops, registry governance, and payment spending controls as first-class concerns, not afterthoughts.
- Never ask users to paste AWS credentials, client secrets, access tokens, account IDs, customer data, or private keys into chat.
- Load only the reference needed for the component in scope.
References
Load these only when needed:
- Workflow and output contract — use for end-to-end AgentCore project, local test, deployment, and output formatting.
- Safety checklist — use before deployment, tool exposure, credential integration, Memory/Gateway changes, or production recommendations.
- Official sources — use when grounding current AgentCore service behavior and docs URLs.
- Getting started — use for project/runtime/harness/local workflow details, direct code deployment, filesystem mounts, and CLI/Inspector caveats, then verify commands against current toolkit version.
- Memory integration — use only for AgentCore Memory resource and agent wiring work.
- Gateway integration — use only for Gateway, MCP tools, and tool target integration.
Response minimum
Return, at minimum:
- the AgentCore component in scope,
- evidence level and docs/tooling used,
- safest next action,
- command or code path to verify,
- security and rollback caveats.
What ships with it: 8 files
40.3 KB alongside SKILL.md
agents/
- openai.yaml742 B
references/
- gateway-integration.md6.4 KB
- getting-started.md6.3 KB
- memory-integration.md5.4 KB
- official-sources.md10.8 KB
- safety-checklist.md3.1 KB
- workflow-and-output.md3.5 KB
- metadata.json3.9 KB