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Hf Cloud Aws Context Discovery

OrganizationPopular
huggingface
hf-cloud-aws-context-discovery

Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration first.

Overview

Publisherhuggingface
Repositoryskills
Skill namehf-cloud-aws-context-discovery
Stars
11.1K
Forks
744
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by huggingface on GitHub. Read the source before you install it.

Installation

Install the Hf Cloud Aws Context Discovery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/huggingface/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/hf-cloud-aws-context-discovery .claude/skills/hf-cloud-aws-context-discovery
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hf Cloud Aws Context Discovery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hf Cloud Aws Context Discovery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hf Cloud Aws Context Discovery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS Context Discovery

Before doing any AWS work, read the user's local AWS config. Don't guess the region, and don't ask the user for things their config already answers.

What to discover

Run these at the start of the AWS work and remember the results for the rest of the session.

1. Active profile

AWS_PROFILE env var, else default. If the user mentioned a profile in their prompt, that overrides. If the named profile doesn't exist in ~/.aws/config, surface that clearly.

2. Region

Resolution order — stop at the first one that produces a value:

  1. Region the user explicitly named in this conversation
  2. AWS_REGION env var
  3. AWS_DEFAULT_REGION env var
  4. region field on the active profile in ~/.aws/config
  5. Ask the user — but only after the first four have failed

Do not fall back to us-east-1 or any other hardcoded default.

3. Credentials, account ID, caller ARN

bash
aws sts get-caller-identity --profile <profile> --region <region>

Three purposes in one call: confirms credentials are valid (stop if not), returns the Account ID (needed for ARN construction), returns the Arn of the caller.

4. Identify SSO / assumed-role principals

The Arn field tells you what kind of principal this is. The pattern matters because it determines what IAM operations the caller can do.

ARN patternTypeIAM write capability
arn:aws:iam::<acct>:user/<name>IAM userDepends on attached policies
arn:aws:sts::<acct>:assumed-role/AWSReservedSSO_<...>/<email>SSO assumed-roleTypically none — can't create/modify IAM roles
arn:aws:sts::<acct>:assumed-role/<role>/<session>Regular assumed-roleDepends on the role

If the caller is SSO, surface this immediately before later skills hit iam:CreateRole and fail:

Heads up: you're authenticated via SSO (AWSReservedSSO_<PermissionSet>_...). SSO principals usually can't create IAM roles directly. If we need a SageMaker execution role, I'll look for an existing one first — if none exists, you'll need to ask whoever manages your AWS access to create one.

This is the highest-leverage thing this skill does. Surfacing it now turns a confusing mid-deployment error into a five-second conversation.

Commands to run

bash
# Effective profile and region (faster than parsing config files)
aws configure list

# Validate credentials and get identity
aws sts get-caller-identity
aws sts get-caller-identity --profile <profile-name>  # if a profile was named

aws configure list handles env-var overrides and shows the resolved effective values. Prefer it over parsing ~/.aws/config yourself. If you need to read raw config (e.g. to list profiles), ~/.aws/config and ~/.aws/credentials are plain INI files — read-only.

What to report back

One or two lines, not a wall of text:

Working with profile my-profile in eu-west-1, account 123456789012. You're authenticated via SSO, so we'll need to use an existing IAM role rather than create one.

Don't ask the user to confirm the region you just read from their config — they configured it; that is the confirmation.

If something is wrong (credentials expired, profile doesn't exist, no region anywhere), stop and surface the specific error before continuing.

Frequently asked questions

What does the Hf Cloud Aws Context Discovery AI skill do?

Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration first.

Why use Hf Cloud Aws Context Discovery on TypingMind?

Because you install it once and use it with any model. Hf Cloud Aws Context Discovery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hf Cloud Aws Context Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/huggingface/skills/tree/main/skills/hf-cloud-aws-context-discovery. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hf Cloud Aws Context Discovery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hf Cloud Aws Context Discovery?

As many as you like. As long as a model supports skills, you can use Hf Cloud Aws Context Discovery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hf Cloud Aws Context Discovery AI skill free?

Yes. It is published on GitHub by huggingface under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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