Official agent skill

Agents Build

by aws in aws/agent-toolkit-for-aws

A skill your agent uses to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal.

OfficialApache-2.0Auto-check: notesAgent Workflows

Install Agents Build

skills CLI
$ npx skills add aws/agent-toolkit-for-aws --skill agents-build -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aws/agent-toolkit-for-aws agents-build --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/aws-agents/skills/agents-build .claude/skills/agents-build && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agents-build
GitHub stars
2.8k
Token cost
~2.3k tokens
SKILL.md length
964 words
Files
14 (incl. scripts, references)
Skills in repo
138
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal.

  • Works in 3 steps: Verify CLI version → Read project context → Determine the workflow
  • Extend an existing agent project with memory
  • SKILL.md covers When to use, Input, Process and Output, plus 1 more section
  • Runs Python scripts from its folder

What it does

Agents Build is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal. Triggers: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "agent auth", "streaming", "VPC", "VPC connectivity", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "migration issue", "change model", "browser tool", "code…

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `references/browser.md`, `references/code-interpreter.md` and `references/integrate.md`).

It sits in Agent Workflows, covering Multi-agent orchestration and Building AI agents. It works with Amazon Bedrock, x402 and LangGraph. The repository describes itself as: Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. The licence is Apache-2.0.

When your agent uses it

  • Extend an existing agent project with memory
  • App integration
  • Code interpreter
  • Resource removal

Example prompts

  • “add memory”
  • “remember across sessions”
  • “call agent from app”
  • “/agents-build”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Verify CLI version
  2. Read project context
  3. Determine the workflow

What it can do on your machine

Read from SKILL.md and the folder at commit bd49cc8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agents Build loads about 2.3k tokens when it runs, and up to ~50k if it reads all its reference files. Until then it costs about 251 tokens; SKILL.md has 964 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~251
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~50k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Grep, Glob, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aws/agent-toolkit-for-aws at commit bd49cc8, republished under its Apache-2.0 licence (© aws). 964 words, ~2,266 tokens.

Download SKILL.mdSave it as .claude/skills/agents-build/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
agents-build
description
Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal. Triggers: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "agent auth", "streaming", "VPC", "VPC connectivity", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "migration issue", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "add payments capability to my agent", "wire payments plugin", "integrate x402 payments with the agent I'm building", "add MPP payments", "Machine Payments Protocol". External APIs via Gateway: use agents-connect. New project: use agents-get-started. CLI/dev-server errors: use agents-debug. Runtime x402/MPP payments: use agents-pay. Migration-specific Strands vs LangGraph routes here.
allowed-tools
Read, Grep, Glob, Bash
metadata.type
skill
metadata.version
1.0.0
metadata.author
aws-agentcore
metadata.requires-cli
>=0.9.0

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
  • Adding AgentCore Payments so the agent can pay for x402- or MPP-protected APIs, tools, or content
  • 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", "payments", "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:

  1. Check if the developer is in the wrong directory. Look for agentcore/agentcore.json in parent directories (up to 3 levels). If found, tell them: "Found an AgentCore project at <path>. Are you working in that project?"
  2. 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, cd into 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 intentReference to load
Add memory, remember things, user preferences, cross-sessionreferences/memory.md
Call agent from app, invoke from code, streaming, SDK client, agent URL, execute shell in sessionreferences/integrate.md
VPC, private network, RDS, internal API, subnet, security groupreferences/vpc.md
Multi-agent, orchestrator, specialist, A2A, delegation, agent handoffreferences/multi-agent.md
Custom headers from caller to agent, header allowlist, tenant ID/correlation ID/trace propagationreferences/request-headers.md
Migrate Bedrock Agent, import agent, move to AgentCorereferences/migrate.md
Browser tool, web navigation, form filling, scraping, Nova Act, Playwright, live viewreferences/browser.md
Code Interpreter, execute code, sandbox, run Python/JS/TS, data analysis in agent, pandasreferences/code-interpreter.md
Payments, pay for x402 or MPP content, 402 Payment Required, Machine Payments Protocol, WWW-Authenticate: Payment, microtransactions, paid API/tool, payment manager/connectorreferences/payments.md
Delete agent, remove resource, tear down, clean up, destroy, start freshreferences/teardown.md
Change model, switch model, use Haiku/Sonnet/Nova, different modelInline — 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.

Show full SKILL.md (330 more words)Show less
Changing the model

The model is configured in app/<AgentName>/model/load.py (scaffolded by agentcore create). To change it:

  1. Open app/<AgentName>/model/load.py
  2. Change the model_id parameter in the BedrockModel() constructor
python
# 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 dev to test locally, then agentcore deploy to 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:

ResourceMax charsAllowedStarts with
Agent (add agent)48alphanumeric + _letter
Memory, gateway, gateway-target, credential, evaluator, online-eval, policy, policy-engine, payment-manager, payment-connector48alphanumeric + _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

© aws, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 13 other files (scripts, references) in plugins/aws-agents/skills/agents-build of aws/agent-toolkit-for-aws.

  • SKILL.md
  • references/browser.md
  • references/code-interpreter.md
  • references/integrate.md
  • references/local-vs-deployed.md
  • references/memory.md
  • references/migrate.md
  • references/multi-agent.md
  • references/payments.md
  • references/request-headers.md
  • references/teardown.md
  • references/vpc.md
  • scripts/process_payment_tool.py
  • scripts/setup_payment_user.py

Open the folder on GitHubat commit bd49cc8

Compare with similar skills

Agents Build next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agents Build compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agents Build this skillaws/agent-toolkit-for-aws2.8k—~2.3kAutomated safety check: NotesApache-2.0
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AWS Strandshoodini/ai-agents-skills282—~1.4kAutomated safety check: PassNone
Langgraph Agent Patternssoba-labs/langchain-agent-skills107—~3.6kAutomated safety check: PassMIT
Multi Agent Architectsickn33/agentic-awesome-skills47k1 repos~3.1kAutomated safety check: PassMIT
Agentsop Agent Topology Selectionagentsope/SkillAlchemy457—~4.7kAutomated safety check: PassMIT

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Questions about Agents Build

What does Agents Build do?

A skill your agent uses to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal. Agents Build is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal.

When should I use Agents Build?

Agents Build fits situations like: extend an existing agent project with memory; app integration; code interpreter; resource removal.

How do I install Agents Build in Claude Code?

Run `npx skills add aws/agent-toolkit-for-aws --skill agents-build -a claude-code`. Or copy the skill folder (plugins/aws-agents/skills/agents-build in aws/agent-toolkit-for-aws) into .claude/skills/agents-build in your project. Claude Code loads it when a task matches its description.

How do I install Agents Build in Codex?

Run `npx skills add aws/agent-toolkit-for-aws --skill agents-build -a codex`. Or copy the skill folder (plugins/aws-agents/skills/agents-build in aws/agent-toolkit-for-aws) into .agents/skills/agents-build in your project. Codex loads it when a task matches its description.

Can I use Agents Build in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws/agent-toolkit-for-aws --skill agents-build -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agents-build, .gemini/skills/agents-build, .github/skills/agents-build and .opencode/skills/agents-build in your project.

What does Agents Build need to run?

Going by SKILL.md and its folder, Agents Build needs Python for the scripts in its folder. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash.

Does Agents Build access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agents Build safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Agents Build use?

Agents Build is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agents Build use?

About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 48k tokens, read only when the agent opens those files.

What are the alternatives to Agents Build?

Skills that share tags, products or a category with Agents Build: AI Agent Development (aiskillstore/marketplace, 430 stars), AWS Strands (hoodini/ai-agents-skills, 282 stars), Langgraph Agent Patterns (soba-labs/langchain-agent-skills, 107 stars) and Multi Agent Architect (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agents Build?

aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,816 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on October 7, 2026.

Source: aws/agent-toolkit-for-aws on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.