AWS S3
majiayu000/claude-skill-registry
Configure S3 buckets, policies, and lifecycle rules. An agent skill from majiayu000/claude-skill-registry.
Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3…
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3 --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .claude/skills/querying-aws-s3 && rm -rf skills-srcUse ~/.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/
Install the "querying-aws-s3" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3 into .claude/skills/querying-aws-s3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-aws-s3", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .agents/skills/querying-aws-s3 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "querying-aws-s3" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3 into .agents/skills/querying-aws-s3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-aws-s3", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .cursor/skills/querying-aws-s3 && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "querying-aws-s3" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3 into .cursor/skills/querying-aws-s3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-aws-s3", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aws/agent-toolkit-for-aws.git --path skills/specialized-skills/system-table-skills/querying-aws-s3--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .gemini/skills/querying-aws-s3 && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "querying-aws-s3" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3 into .gemini/skills/querying-aws-s3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-aws-s3", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .github/skills/querying-aws-s3 && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "querying-aws-s3" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3 into .github/skills/querying-aws-s3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-aws-s3", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aws/agent-toolkit-for-aws querying-aws-s3 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/specialized-skills/system-table-skills/querying-aws-s3 .opencode/skills/querying-aws-s3 && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "querying-aws-s3" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/system-table-skills/querying-aws-s3 into .opencode/skills/querying-aws-s3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-aws-s3", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
querying-aws-s3Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3…
Querying AWS S3 is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking down storage classes, finding objects by tag, searching annotation content, analyzing storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw…
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Backend & APIs, covering File uploads and storage. It works with Amazon S3, Amazon Web Services and SQL. 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.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 188af2f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
awsFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
docs.aws.amazon.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Querying AWS S3 loads about 3.3k tokens when it runs. Until then it costs about 191 tokens; SKILL.md has 916 words of instructions outside code blocks.
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.
The automated check found no risky patterns in SKILL.md.
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); files beside SKILL.md are not scanned.
The full file from aws/agent-toolkit-for-aws at commit 188af2f, republished under its Apache-2.0 licence (© aws). 916 words, ~3,291 tokens.
.claude/skills/querying-aws-s3/SKILL.md (or your agent's skills folder).Works best with the AWS MCP server for sandboxed execution and audit logging. All commands below use the AWS CLI and work in any environment with configured AWS credentials. Use IAM roles or temporary credentials; avoid long-lived access keys.
Amazon S3 Metadata provides continuously-updated Apache Iceberg tables that capture
object-level metadata for general-purpose buckets. S3 Storage Lens exports aggregated
storage and activity metrics as Iceberg tables. Both are read-only, stored in the
AWS-managed aws-s3 table bucket, and queryable via Amazon Athena.
System tables are preferred over raw S3 APIs (list-objects-v2, head-object) because:
list-objects-v2 paginates at 1000 objects/page — inefficient for large buckets (millions or billions of objects). The inventory table answers SELECT COUNT(*) in seconds at any scale.list-objects-v2 cannot identify who uploaded an object, from which IP, or when something was deleted. Only the journal table has requester, source_ip_address, and delete event tracking.get-object-tagging per object. The inventory table has object_tags as a queryable map column.| User intent | Use this skill? | Table | Alternative |
|---|---|---|---|
| How many objects in my bucket | Yes | inventory | — |
| What was recently uploaded/deleted | Yes | journal | — |
| Who wrote/deleted objects (audit) | Yes | journal (requester, source_ip) | — |
| Storage class breakdown | Yes | inventory | — |
| Find objects by tag or user metadata | Yes | inventory | — |
| Search annotation content | Yes | annotation | Single object → direct API get-object-annotation |
| Write/update an annotation | No | — | Direct API: put-object-annotation (tables are read-only) |
| Query data inside objects | No | — | querying-data-lake |
| Bucket-level storage metrics/trends | Yes | Storage Lens tables | — |
| Enable metadata tracking | Yes | see Enable section | — |
Before querying, confirm S3 Metadata is enabled on the target bucket.
aws s3api get-bucket-metadata-configuration --bucket <BUCKET> --region <REGION>Interpret the response:
MetadataConfigurationNotFound error → not enabled. See Enable section below.TableStatus: ACTIVE → ready to query.TableStatus: BACKFILLING → queryable but inventory may be incomplete.TableStatus: FAILED → check error field (usually IAM).For Storage Lens:
aws s3control get-storage-lens-configuration --account-id <ACCOUNT> --config-id <CONFIG_ID> --region <REGION>Look for DataExport.StorageLensTableDestination.IsEnabled: true.
Enable S3 Metadata on a bucket:
aws s3api create-bucket-metadata-configuration \
--bucket <BUCKET> \
--region <REGION> \
--metadata-configuration '{
"JournalTableConfiguration": {"RecordExpiration": {"Expiration": "DISABLED"}},
"InventoryTableConfiguration": {"ConfigurationState": "ENABLED"}
}'To also enable annotations (requires a service role):
aws s3api create-bucket-metadata-configuration \
--bucket <BUCKET> \
--region <REGION> \
--metadata-configuration '{
"JournalTableConfiguration": {"RecordExpiration": {"Expiration": "ENABLED", "Days": 90}},
"InventoryTableConfiguration": {"ConfigurationState": "ENABLED"},
"AnnotationTableConfiguration": {"ConfigurationState": "ENABLED", "Role": "<ROLE_ARN>"}
}'Enable Storage Lens S3 Tables export:
aws s3control put-storage-lens-configuration \
--account-id <ACCOUNT> \
--config-id <CONFIG_ID> \
--region <REGION> \
--storage-lens-configuration '{
"Id": "<CONFIG_ID>",
"IsEnabled": true,
"AccountLevel": {"BucketLevel": {}},
"DataExport": {
"StorageLensTableDestination": {"IsEnabled": true}
}
}'Register S3 Tables federated catalog in Glue (required for Athena access):
aws glue create-catalog --region <REGION> --cli-input-json '{
"Name": "s3tablescatalog",
"CatalogInput": {
"FederatedCatalog": {
"Identifier": "arn:aws:s3tables:<REGION>:<ACCOUNT>:bucket/*",
"ConnectionName": "aws:s3tables"
}
}
}'For setup permissions and IAM role requirements, see Security Considerations below.
Querying requires:
s3tablescatalog)If CATALOG_NOT_FOUND errors occur, the Glue integration may not be enabled. See:
Integrating S3 Tables with AWS analytics services
S3 Metadata tables — namespace is b_<bucket-name>:
| Table | What it captures |
|---|---|
journal | Event log — every CREATE, DELETE, UPDATE_METADATA, and annotation events. Near real-time. |
inventory | Current state — one row per object (latest version). Updates within 1 hour. |
annotation | Annotation payloads — text_value column holds the full content. Near real-time. |
Storage Lens tables — namespace is lens_<config-id>_exp:
| Table | What it captures |
|---|---|
default_storage_metrics | Per-bucket/prefix: object count, size, storage class breakdown. Daily. |
default_activity_metrics | Per-bucket/prefix: GET/PUT/DELETE request counts. Daily. |
bucket_property_metrics | Bucket config: versioning, encryption, lifecycle settings. Daily. |
Query syntax:
"s3tablescatalog/aws-s3"."<namespace>"."<table>"Constraints:
You MUST confirm workgroup and output location before executing
You MUST ensure the Athena workgroup enforces SSE-KMS encryption on query results
You MUST warn user that tables are read-only — no INSERT/UPDATE/DELETE
You SHOULD use the key columns documented in this skill to build queries. If you need the full schema (e.g., AWS has added new columns), run get-tables once on any single namespace — schemas are identical across all instances of the same table type:
aws glue get-tables --catalog-id "<ACCOUNT>:s3tablescatalog/aws-s3" --database-name "<namespace>" --region <REGION>Journal — audit who changed what:
SELECT key, record_type, record_timestamp, requester, source_ip_address
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."journal"
WHERE record_type = 'DELETE'
AND record_timestamp > current_timestamp - interval '24' hour
ORDER BY record_timestamp DESC;Journal — track annotation events:
SELECT key, record_type, annotation.name, record_timestamp
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."journal"
WHERE record_type IN ('CREATE_ANNOTATION', 'DELETE_ANNOTATION', 'UPDATE_ANNOTATION_METADATA')
ORDER BY record_timestamp DESC LIMIT 20;Inventory — find objects by storage class:
SELECT key, size, storage_class, last_modified_date
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."inventory"
WHERE storage_class = 'GLACIER'
ORDER BY size DESC LIMIT 50;Inventory — find objects by tag:
SELECT key, size, object_tags
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."inventory"
WHERE object_tags['environment'] = 'staging';Annotation — search across payloads:
SELECT object_key, name, text_value
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."annotation"
WHERE text_value LIKE '%error%';Annotation — extract JSON fields:
SELECT object_key, json_extract_scalar(text_value, '$.status') as status
FROM "s3tablescatalog/aws-s3"."b_<bucket>"."annotation"
WHERE name = 'pipeline_status'
AND json_extract_scalar(text_value, '$.status') = 'FAILED';Storage Lens — storage distribution:
SELECT *
FROM "s3tablescatalog/aws-s3"."lens_<config-id>_exp"."default_storage_metrics"
LIMIT 20;| Scenario | Use |
|---|---|
| Single known object + annotation name | Direct API: get-object-annotation |
| Aggregate/count across many objects | Athena on annotation or inventory table |
| Full-text search across annotation payloads | Athena with LIKE or json_extract_scalar |
| Write/update an annotation | Direct API: put-object-annotation (table is read-only) |
| Feature not configured on bucket | Direct API loop (list-objects-v2 + head-object); suggest enabling S3 Metadata |
| Error | Cause | Fix |
|---|---|---|
CATALOG_NOT_FOUND | S3 Tables not registered in Glue | Enable integration: S3 console > Table buckets > Enable integration |
| Empty results from journal | Feature just enabled; no events recorded yet | Upload/delete an object and wait ~1 minute |
| Empty results from inventory | Table still BACKFILLING | Check status; wait for ACTIVE (minutes to hours depending on object count) |
AccessDenied querying table | Missing s3tables:GetTable or GetTableMetadataLocation | See Security Considerations below |
| Wrong namespace | Bucket name has periods | Periods are converted to underscores in namespace: my.bucket → b_my_bucket |
| No Storage Lens data | First delivery takes up to 48 hours | Wait; no historical backfill |
Scope permissions to specific table bucket ARNs rather than using wildcards:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3tables:GetTable",
"s3tables:GetTableMetadataLocation",
"s3tables:GetTableData",
"s3tables:GetNamespace",
"s3tables:ListTables",
"s3tables:ListNamespaces",
"s3tables:GetTableBucket"
],
"Resource": [
"arn:aws:s3tables:<REGION>:<ACCOUNT>:bucket/aws-s3",
"arn:aws:s3tables:<REGION>:<ACCOUNT>:bucket/aws-s3/*"
]
}
]
}Journal query results may contain sensitive fields:
requester — AWS account ID or service principal that made the requestsource_ip_address — IP address of the requesterQuery results containing these fields should be stored in encrypted, access-controlled locations. Avoid logging or sharing raw query output that contains IP addresses or principal identifiers.
Configure the Athena workgroup with EncryptionConfiguration to encrypt query results at rest:
{
"ResultConfiguration": {
"EncryptionConfiguration": {
"EncryptionOption": "SSE_KMS",
"KmsKey": "arn:aws:kms:<REGION>:<ACCOUNT>:key/<KEY_ID>"
}
}
}Enable CloudTrail logging for Athena (StartQueryExecution, GetQueryResults) and S3 Tables (s3tables:GetTableData) API calls to maintain an audit trail of who queried what metadata. Ensure CloudTrail logs are encrypted with SSE-KMS and stored in a bucket with access logging enabled.
© 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
Just SKILL.md in skills/specialized-skills/system-table-skills/querying-aws-s3 of aws/agent-toolkit-for-aws.
Open the folder on GitHubat commit 188af2f
Querying AWS S3 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Querying AWS S3 this skillaws/agent-toolkit-for-aws | 2.8k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| AWS S3majiayu000/claude-skill-registry | 666 | 3 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Django Storages for S3Jeffallan/claude-skills | 12k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Neon Object Storageneondatabase/agent-skills | 100 | — | ~3.5k | Automated safety check: Notes | Apache-2.0 | |
| S3itsmostafa/aws-agent-skills | 1.2k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Remediating S3 Bucket Misconfigurationmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~3k | Automated safety check: Pass | Apache-2.0 |
majiayu000/claude-skill-registry
Configure S3 buckets, policies, and lifecycle rules. An agent skill from majiayu000/claude-skill-registry.
Jeffallan/claude-skills
Sets up Django 4.2+ to keep static and media files on AWS S3 through django-storages, with public and private backends, presigned URLs and CloudFront.
neondatabase/agent-skills
S3-compatible object storage that branches with your Neon project, so files and the database stay in sync across every branch.
itsmostafa/aws-agent-skills
AWS S3 object storage for bucket management, object operations, and access control.
mukul975/Anthropic-Cybersecurity-Skills
Provides step-by-step procedures for remediating Amazon S3 bucket misconfigurations that expose sensitive data: enabling S3 Block Public Access, auditing bucket policies and ACLs, enforcing…
giuseppe-trisciuoglio/developer-kit
Provides Amazon S3 patterns and examples using AWS SDK for Java 2.x.
aws/agent-toolkit-for-aws
Entry point for AI-agent work on AWS: pick a runtime, plan a migration for existing workloads, and build an executable POC — one phased flow.
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.
aws/agent-toolkit-for-aws
Migrates vibe-coded web applications to AWS. An agent skill from aws/agent-toolkit-for-aws.
aws/agent-toolkit-for-aws
Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size.
aws/agent-toolkit-for-aws
Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses…
aws/agent-toolkit-for-aws
A skill your agent uses when THIS agent needs to pay for x402-protected content at runtime: hitting a paywall mid-task, settling it via AgentCore Payments, and applying operator-defined spend limits.
Works with
Categories
Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3…. Querying AWS S3 is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL.
Querying AWS S3 fits situations like: phrases: bucket activity; track deletions; storage class breakdown; search annotations.
Run `npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a claude-code`. Or copy the skill folder (skills/specialized-skills/system-table-skills/querying-aws-s3 in aws/agent-toolkit-for-aws) into .claude/skills/querying-aws-s3 in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aws/agent-toolkit-for-aws --skill querying-aws-s3 -a codex`. Or copy the skill folder (skills/specialized-skills/system-table-skills/querying-aws-s3 in aws/agent-toolkit-for-aws) into .agents/skills/querying-aws-s3 in your project. Codex loads it when a task matches its description.
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 querying-aws-s3 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/querying-aws-s3, .gemini/skills/querying-aws-s3, .github/skills/querying-aws-s3 and .opencode/skills/querying-aws-s3 in your project.
Going by SKILL.md and its folder, Querying AWS S3 needs the command-line tools its instructions call (aws).
SKILL.md names 1 domain. As links in the text: docs.aws.amazon.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Querying AWS S3 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.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Querying AWS S3: AWS S3 (majiayu000/claude-skill-registry, 666 stars), Django Storages for S3 (Jeffallan/claude-skills, 12k stars), Neon Object Storage (neondatabase/agent-skills, 100 stars) and S3 (itsmostafa/aws-agent-skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,825 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.