agents-build
Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.
下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o agents-build.zip https://jpskill.com/download/23323.zip && unzip -o agents-build.zip && rm agents-build.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/23323.zip -OutFile "$d\agents-build.zip"; Expand-Archive "$d\agents-build.zip" -DestinationPath $d -Force; ri "$d\agents-build.zip"
完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。
💾 手動でダウンロードしたい(コマンドが難しい人向け)
- 1. 下の青いボタンを押して
agents-build.zipをダウンロード - 2. ZIPファイルをダブルクリックで解凍 →
agents-buildフォルダができる - 3. そのフォルダを
C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-18
- 取得日時
- 2026-05-18
- 同梱ファイル
- 11
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
build
Add capabilities to your AgentCore agent project.
When to use
- Adding cross-session memory to your agent
- Calling your deployed agent from a web app, mobile app, or backend service
- Configuring VPC networking for private resources (RDS, internal APIs)
- Building multi-agent systems with orchestrator/specialist patterns
- Migrating an existing Bedrock Agent to AgentCore
- Adding the Browser tool so the agent can navigate websites
- Adding the Code Interpreter so the agent can execute code in a sandbox
- Removing resources from your project or tearing down a deployment
Do NOT use for:
- Connecting to external tools/APIs via Gateway (OpenAPI specs, Lambda, MCP servers, credentials, policies) → use
agents-connect - Scaffolding a new project → use
agents-get-started - Deploying → use
agents-deploy
Input
$ARGUMENTS can be:
- A capability: "memory", "integrate", "vpc", "multi-agent", "migrate", "browser", "code-interpreter", "teardown"
- A description of what they want: "remember user preferences", "call from React app", "scrape a website", "run pandas in the agent", "delete my agent", "clean up resources"
- Empty — the skill will determine the workflow from context
Process
Step 0: Verify CLI version
Run agentcore --version. This skill requires v0.9.0 or later.
If older: "Run agentcore update to get the latest version."
Step 1: Read project context
Read agentcore/agentcore.json to understand the current project — framework, existing resources, agent configuration.
If agentcore/agentcore.json is not found:
- Check if the developer is in the wrong directory. Look for
agentcore/agentcore.jsonin parent directories (up to 3 levels). If found, tell them: "Found an AgentCore project at<path>. Are you working in that project?" - If no project exists anywhere nearby, ask what capability they wanted to add. Then offer two paths:
- "I can walk you through creating a project first and then adding CAPABILITY — want to do that?" (run the get-started flow inline, then continue with the build workflow)
- "If you already have a project elsewhere,
cdinto it and try again."
Do not just say "go use agents-get-started" and stop — that loses the developer's context about what they actually wanted to do.
Step 2: Determine the workflow
Important disambiguation — before routing to a build reference, check if the prompt is actually a connect or debug concern:
- If the phrase mentions external APIs, Lambda functions, OpenAPI specs, gateways, credentials, MCP servers, or policies → this is
agents-connect, not build - If the developer says something is broken (wrong answers, errors, tool failures) → this is
agents-debug, not build - Build is for adding new capabilities to a working project, not fixing broken ones
Based on the developer's prompt and $ARGUMENTS, load the appropriate reference:
| Developer intent | Reference to load |
|---|---|
| Add memory, remember things, user preferences, cross-session | references/memory.md |
| Call agent from app, invoke from code, streaming, SDK client, agent URL, execute shell in session | references/integrate.md |
| VPC, private network, RDS, internal API, subnet, security group | references/vpc.md |
| Multi-agent, orchestrator, specialist, A2A, delegation, agent handoff | references/multi-agent.md |
| Custom headers from caller to agent, header allowlist, tenant ID/correlation ID/trace propagation | references/request-headers.md |
| Migrate Bedrock Agent, import agent, move to AgentCore | references/migrate.md |
| Browser tool, web navigation, form filling, scraping, Nova Act, Playwright, live view | references/browser.md |
| Code Interpreter, execute code, sandbox, run Python/JS/TS, data analysis in agent, pandas | references/code-interpreter.md |
| Delete agent, remove resource, tear down, clean up, destroy, start fresh | references/teardown.md |
| Change model, switch model, use Haiku/Sonnet/Nova, different model | Inline — see "Changing the model" below |
If the developer asks about the difference between local dev and deployed (e.g., "why does my memory work after deploy but not locally?"), load references/local-vs-deployed.md alongside the specific workflow reference.
Read the matching file into context and follow its Process section step by step — do not summarize.
If the intent is ambiguous, ask the developer which capability they want to add.
Changing the model
The model is configured in app/<AgentName>/model/load.py (scaffolded by agentcore create). To change it:
- Open
app/<AgentName>/model/load.py - Change the
model_idparameter in theBedrockModel()constructor
# Default (scaffolded by CLI)
return BedrockModel(model_id="global.anthropic.claude-sonnet-4-5-20250929-v1:0")
# Switch to Haiku for cost savings
return BedrockModel(model_id="us.anthropic.claude-3-5-haiku-20241022-v1:0")
# Switch to Nova Lite
return BedrockModel(model_id="amazon.nova-lite-v1:0")
Cross-region inference profile prefixes (us., eu., apac., global.) control where inference runs. Use global. for maximum throughput, or a geographic prefix for data residency. Not all models support all prefixes — check the Bedrock inference profiles docs.
After changing the model:
- Verify the model is enabled in your region: AWS Console → Amazon Bedrock → Model access
- For cross-region profiles, enable in all destination regions
- If using
agents-harden, update the IAM policy to scope to the new model ARN - Run
agentcore devto test locally, thenagentcore deployto update the deployed agent
No agentcore.json change is needed — the model is configured in code, not in the project config.
Pre-flight: validate any --name before generating the CLI command
Whichever reference you load, most end up producing an agentcore add <resource> --name <something> command. The CLI fails late on invalid names — you'll see the error after walking through prompts, not before running the command. Validate up front:
| Resource | Max chars | Allowed | Starts with |
|---|---|---|---|
Agent (add agent) |
48 | alphanumeric + _ |
letter |
| Memory, gateway, gateway-target, credential, evaluator, online-eval, policy, policy-engine | 48 | alphanumeric + _ |
letter |
Count the characters before constructing the command. If the name is over the limit or contains hyphens, dots, or spaces, push back: "<name> is N characters / uses -, which the CLI rejects. How about <suggestion>?" Never run the command with an invalid name hoping the CLI message will be clear.
Note: agentcore create --name (the project name) has a stricter 23-char limit and does not allow underscores. That's covered in agents-get-started; if you see the developer re-running create, flag the 23-char limit specifically.
Output
Depends on the workflow — see the loaded reference for specific outputs.
Quality criteria
- The correct reference was loaded based on the developer's intent
- All output follows the loaded reference's quality criteria
- Cross-references to other skills (agents-connect, agents-deploy) are included where relevant
同梱ファイル
※ ZIPに含まれるファイル一覧。`SKILL.md` 本体に加え、参考資料・サンプル・スクリプトが入っている場合があります。
- 📄 SKILL.md (8,696 bytes)
- 📎 references/browser.md (10,283 bytes)
- 📎 references/code-interpreter.md (9,075 bytes)
- 📎 references/integrate.md (19,521 bytes)
- 📎 references/local-vs-deployed.md (4,297 bytes)
- 📎 references/memory.md (28,339 bytes)
- 📎 references/migrate.md (5,638 bytes)
- 📎 references/multi-agent.md (16,566 bytes)
- 📎 references/request-headers.md (6,939 bytes)
- 📎 references/teardown.md (5,473 bytes)
- 📎 references/vpc.md (12,813 bytes)