[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-aws-querying-aws-s3":3,"mdc--cstzt4-key":35,"related-repo-aws-querying-aws-s3":3098,"related-org-aws-querying-aws-s3":3204},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":24,"repoUrl":25,"updatedAt":26,"license":27,"forks":28,"topics":29,"repo":30,"sourceUrl":33,"mdContent":34},"querying-aws-s3","query AWS S3 metadata and metrics","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 S3 APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"aws","AWS (Amazon)","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Faws.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Audit","audit","tag",{"name":17,"slug":18,"type":15},"Data Analysis","data-analysis",{"name":20,"slug":21,"type":15},"Storage","storage",{"name":23,"slug":8,"type":15},"AWS",1822,"https:\u002F\u002Fgithub.com\u002Faws\u002Fagent-toolkit-for-aws","2026-07-12T08:43:47.628138",null,157,[],{"repoUrl":25,"stars":24,"forks":28,"topics":31,"description":32},[],"Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS","https:\u002F\u002Fgithub.com\u002Faws\u002Fagent-toolkit-for-aws\u002Ftree\u002FHEAD\u002Fskills\u002Fspecialized-skills\u002Fsystem-table-skills\u002Fquerying-aws-s3","---\nname: querying-aws-s3\ndescription: >-\n  Queries S3 object metadata, tracks bucket activity, audits object changes, searches\n  annotations, and analyzes storage metrics using S3 Metadata system tables (journal,\n  inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting\n  objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking\n  down storage classes, finding objects by tag, searching annotation content, analyzing\n  storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw S3\n  APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object\n  count, who uploaded, track deletions, storage class breakdown, find by tag, search\n  annotations, storage lens metrics, audit bucket changes.\nversion: 1\nargument-hint: \"[bucket-name|query|'configure BUCKET'|'status BUCKET']\"\n---\n\n# Query AWS S3 System Tables\n\n## Overview\n\n**Works best with** the [AWS MCP server](https:\u002F\u002Fdocs.aws.amazon.com\u002Fagent-toolkit\u002Flatest\u002Fuserguide\u002Fgetting-started-aws-mcp-server.html) 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.\n\nAmazon S3 Metadata provides continuously-updated Apache Iceberg tables that capture\nobject-level metadata for general-purpose buckets. S3 Storage Lens exports aggregated\nstorage and activity metrics as Iceberg tables. Both are read-only, stored in the\nAWS-managed `aws-s3` table bucket, and queryable via Amazon Athena.\n\nSystem tables are preferred over raw S3 APIs (`list-objects-v2`, `head-object`) because:\n\n- `list-objects-v2` paginates at 1000 objects\u002Fpage — inefficient for large buckets (millions or billions of objects). The inventory table answers `SELECT COUNT(*)` in seconds at any scale.\n- `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.\n- Filtering by tag requires `get-object-tagging` per object. The inventory table has `object_tags` as a queryable map column.\n\n## Decision Tree\n\n| User intent | Use this skill? | Table | Alternative |\n|---|---|---|---|\n| How many objects in my bucket | **Yes** | inventory | — |\n| What was recently uploaded\u002Fdeleted | **Yes** | journal | — |\n| Who wrote\u002Fdeleted objects (audit) | **Yes** | journal (requester, source_ip) | — |\n| Storage class breakdown | **Yes** | inventory | — |\n| Find objects by tag or user metadata | **Yes** | inventory | — |\n| Search annotation content | **Yes** | annotation | Single object → direct API `get-object-annotation` |\n| Write\u002Fupdate an annotation | **No** | — | Direct API: `put-object-annotation` (tables are read-only) |\n| Query data *inside* objects | **No** | — | `querying-data-lake` |\n| Bucket-level storage metrics\u002Ftrends | **Yes** | Storage Lens tables | — |\n| Enable metadata tracking | **Yes** | see Enable section | — |\n\n## Common Tasks\n\n### 1. Check If Configured\n\nBefore querying, confirm S3 Metadata is enabled on the target bucket.\n\n```bash\naws s3api get-bucket-metadata-configuration --bucket \u003CBUCKET> --region \u003CREGION>\n```\n\n**Interpret the response:**\n\n- `MetadataConfigurationNotFound` error → not enabled. See Enable section below.\n- `TableStatus: ACTIVE` → ready to query.\n- `TableStatus: BACKFILLING` → queryable but inventory may be incomplete.\n- `TableStatus: FAILED` → check error field (usually IAM).\n\n**For Storage Lens:**\n\n```bash\naws s3control get-storage-lens-configuration --account-id \u003CACCOUNT> --config-id \u003CCONFIG_ID> --region \u003CREGION>\n```\n\nLook for `DataExport.StorageLensTableDestination.IsEnabled: true`.\n\n### 2. Enable (if not configured)\n\n**Enable S3 Metadata on a bucket:**\n\n```bash\naws s3api create-bucket-metadata-configuration \\\n  --bucket \u003CBUCKET> \\\n  --region \u003CREGION> \\\n  --metadata-configuration '{\n    \"JournalTableConfiguration\": {\"RecordExpiration\": {\"Expiration\": \"DISABLED\"}},\n    \"InventoryTableConfiguration\": {\"ConfigurationState\": \"ENABLED\"}\n  }'\n```\n\nTo also enable annotations (requires a service role):\n\n```bash\naws s3api create-bucket-metadata-configuration \\\n  --bucket \u003CBUCKET> \\\n  --region \u003CREGION> \\\n  --metadata-configuration '{\n    \"JournalTableConfiguration\": {\"RecordExpiration\": {\"Expiration\": \"ENABLED\", \"Days\": 90}},\n    \"InventoryTableConfiguration\": {\"ConfigurationState\": \"ENABLED\"},\n    \"AnnotationTableConfiguration\": {\"ConfigurationState\": \"ENABLED\", \"Role\": \"\u003CROLE_ARN>\"}\n  }'\n```\n\n**Enable Storage Lens S3 Tables export:**\n\n```bash\naws s3control put-storage-lens-configuration \\\n  --account-id \u003CACCOUNT> \\\n  --config-id \u003CCONFIG_ID> \\\n  --region \u003CREGION> \\\n  --storage-lens-configuration '{\n    \"Id\": \"\u003CCONFIG_ID>\",\n    \"IsEnabled\": true,\n    \"AccountLevel\": {\"BucketLevel\": {}},\n    \"DataExport\": {\n      \"StorageLensTableDestination\": {\"IsEnabled\": true}\n    }\n  }'\n```\n\n**Register S3 Tables federated catalog in Glue** (required for Athena access):\n\n```bash\naws glue create-catalog --region \u003CREGION> --cli-input-json '{\n  \"Name\": \"s3tablescatalog\",\n  \"CatalogInput\": {\n    \"FederatedCatalog\": {\n      \"Identifier\": \"arn:aws:s3tables:\u003CREGION>:\u003CACCOUNT>:bucket\u002F*\",\n      \"ConnectionName\": \"aws:s3tables\"\n    }\n  }\n}'\n```\n\nFor setup permissions and IAM role requirements, see [Security Considerations](#security-considerations) below.\n\n### 3. Verify Permissions\n\nQuerying requires:\n\n- Athena execution permissions\n- S3 Tables read permissions (see least-privilege policy in Security Considerations)\n- The S3 Tables federated catalog registered in Glue (`s3tablescatalog`)\n- Athena workgroup with SSE-KMS encryption configured on the output location\n\nIf `CATALOG_NOT_FOUND` errors occur, the Glue integration may not be enabled. See:\n[Integrating S3 Tables with AWS analytics services](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fs3-tables-integrating-aws.html)\n\n### 4. Identify the Target Table\n\n**S3 Metadata tables** — namespace is `b_\u003Cbucket-name>`:\n\n| Table | What it captures |\n|-------|-----------------|\n| `journal` | Event log — every CREATE, DELETE, UPDATE_METADATA, and annotation events. Near real-time. |\n| `inventory` | Current state — one row per object (latest version). Updates within 1 hour. |\n| `annotation` | Annotation payloads — `text_value` column holds the full content. Near real-time. |\n\n**Storage Lens tables** — namespace is `lens_\u003Cconfig-id>_exp`:\n\n| Table | What it captures |\n|-------|-----------------|\n| `default_storage_metrics` | Per-bucket\u002Fprefix: object count, size, storage class breakdown. Daily. |\n| `default_activity_metrics` | Per-bucket\u002Fprefix: GET\u002FPUT\u002FDELETE request counts. Daily. |\n| `bucket_property_metrics` | Bucket config: versioning, encryption, lifecycle settings. Daily. |\n\n### 5. Query\n\n**Query syntax:**\n\n```sql\n\"s3tablescatalog\u002Faws-s3\".\"\u003Cnamespace>\".\"\u003Ctable>\"\n```\n\n**Constraints:**\n\n- You MUST confirm workgroup and output location before executing\n- You MUST ensure the Athena workgroup enforces SSE-KMS encryption on query results\n- You MUST warn user that tables are read-only — no INSERT\u002FUPDATE\u002FDELETE\n- 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:\n\n  ```\n  aws glue get-tables --catalog-id \"\u003CACCOUNT>:s3tablescatalog\u002Faws-s3\" --database-name \"\u003Cnamespace>\" --region \u003CREGION>\n  ```\n\n**Journal — audit who changed what:**\n\n```sql\nSELECT key, record_type, record_timestamp, requester, source_ip_address\nFROM \"s3tablescatalog\u002Faws-s3\".\"b_\u003Cbucket>\".\"journal\"\nWHERE record_type = 'DELETE'\n  AND record_timestamp > current_timestamp - interval '24' hour\nORDER BY record_timestamp DESC;\n```\n\n**Journal — track annotation events:**\n\n```sql\nSELECT key, record_type, annotation.name, record_timestamp\nFROM \"s3tablescatalog\u002Faws-s3\".\"b_\u003Cbucket>\".\"journal\"\nWHERE record_type IN ('CREATE_ANNOTATION', 'DELETE_ANNOTATION', 'UPDATE_ANNOTATION_METADATA')\nORDER BY record_timestamp DESC LIMIT 20;\n```\n\n**Inventory — find objects by storage class:**\n\n```sql\nSELECT key, size, storage_class, last_modified_date\nFROM \"s3tablescatalog\u002Faws-s3\".\"b_\u003Cbucket>\".\"inventory\"\nWHERE storage_class = 'GLACIER'\nORDER BY size DESC LIMIT 50;\n```\n\n**Inventory — find objects by tag:**\n\n```sql\nSELECT key, size, object_tags\nFROM \"s3tablescatalog\u002Faws-s3\".\"b_\u003Cbucket>\".\"inventory\"\nWHERE object_tags['environment'] = 'staging';\n```\n\n**Annotation — search across payloads:**\n\n```sql\nSELECT object_key, name, text_value\nFROM \"s3tablescatalog\u002Faws-s3\".\"b_\u003Cbucket>\".\"annotation\"\nWHERE text_value LIKE '%error%';\n```\n\n**Annotation — extract JSON fields:**\n\n```sql\nSELECT object_key, json_extract_scalar(text_value, '$.status') as status\nFROM \"s3tablescatalog\u002Faws-s3\".\"b_\u003Cbucket>\".\"annotation\"\nWHERE name = 'pipeline_status'\n  AND json_extract_scalar(text_value, '$.status') = 'FAILED';\n```\n\n**Storage Lens — storage distribution:**\n\n```sql\nSELECT *\nFROM \"s3tablescatalog\u002Faws-s3\".\"lens_\u003Cconfig-id>_exp\".\"default_storage_metrics\"\nLIMIT 20;\n```\n\n### Routing: Athena vs Direct API\n\n| Scenario | Use |\n|----------|-----|\n| Single known object + annotation name | Direct API: `get-object-annotation` |\n| Aggregate\u002Fcount across many objects | Athena on annotation or inventory table |\n| Full-text search across annotation payloads | Athena with `LIKE` or `json_extract_scalar` |\n| Write\u002Fupdate an annotation | Direct API: `put-object-annotation` (table is read-only) |\n| Feature not configured on bucket | Direct API loop (`list-objects-v2` + `head-object`); suggest enabling S3 Metadata |\n\n## Troubleshooting\n\n| Error | Cause | Fix |\n|-------|-------|-----|\n| `CATALOG_NOT_FOUND` | S3 Tables not registered in Glue | Enable integration: S3 console > Table buckets > Enable integration |\n| Empty results from journal | Feature just enabled; no events recorded yet | Upload\u002Fdelete an object and wait ~1 minute |\n| Empty results from inventory | Table still `BACKFILLING` | Check status; wait for ACTIVE (minutes to hours depending on object count) |\n| `AccessDenied` querying table | Missing `s3tables:GetTable` or `GetTableMetadataLocation` | See Security Considerations below |\n| Wrong namespace | Bucket name has periods | Periods are converted to underscores in namespace: `my.bucket` → `b_my_bucket` |\n| No Storage Lens data | First delivery takes up to 48 hours | Wait; no historical backfill |\n\n## Security Considerations\n\n### Least-Privilege IAM Policy\n\nScope permissions to specific table bucket ARNs rather than using wildcards:\n\n```json\n{\n  \"Version\": \"2012-10-17\",\n  \"Statement\": [\n    {\n      \"Effect\": \"Allow\",\n      \"Action\": [\n        \"s3tables:GetTable\",\n        \"s3tables:GetTableMetadataLocation\",\n        \"s3tables:GetTableData\",\n        \"s3tables:GetNamespace\",\n        \"s3tables:ListTables\",\n        \"s3tables:ListNamespaces\",\n        \"s3tables:GetTableBucket\"\n      ],\n      \"Resource\": [\n        \"arn:aws:s3tables:\u003CREGION>:\u003CACCOUNT>:bucket\u002Faws-s3\",\n        \"arn:aws:s3tables:\u003CREGION>:\u003CACCOUNT>:bucket\u002Faws-s3\u002F*\"\n      ]\n    }\n  ]\n}\n```\n\n### Data Sensitivity\n\nJournal query results may contain sensitive fields:\n\n- `requester` — AWS account ID or service principal that made the request\n- `source_ip_address` — IP address of the requester\n\nQuery 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.\n\n### Encryption for Query Results\n\nConfigure the Athena workgroup with `EncryptionConfiguration` to encrypt query results at rest:\n\n```json\n{\n  \"ResultConfiguration\": {\n    \"EncryptionConfiguration\": {\n      \"EncryptionOption\": \"SSE_KMS\",\n      \"KmsKey\": \"arn:aws:kms:\u003CREGION>:\u003CACCOUNT>:key\u002F\u003CKEY_ID>\"\n    }\n  }\n}\n```\n\n### Audit Trail\n\nEnable 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.\n\n## Additional Resources\n\n- [S3 Metadata overview](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fmetadata-tables-overview.html)\n- [Journal table schema](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fmetadata-tables-schema.html)\n- [Inventory table schema](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fmetadata-tables-inventory-schema.html)\n- [Example metadata queries](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fmetadata-tables-example-queries.html)\n- [S3 Annotations overview](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fannotations-overview.html)\n- [Storage Lens S3 Tables export](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fstorage-lens-s3-tables-naming.html)\n- [Setting up permissions](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fmetadata-tables-permissions.html)\n- [Integrating S3 Tables with AWS analytics services](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonS3\u002Flatest\u002Fuserguide\u002Fs3-tables-integrating-aws.html)\n",{"data":36,"body":39},{"name":4,"description":6,"version":37,"argument-hint":38},1,"[bucket-name|query|'configure BUCKET'|'status BUCKET']",{"type":40,"children":41},"root",[42,51,58,81,95,116,185,191,497,503,510,515,598,606,653,661,750,763,769,777,914,919,1050,1058,1247,1257,1381,1394,1400,1405,1436,1456,1462,1480,1557,1572,1643,1649,1657,1673,1681,1722,1730,1777,1785,1823,1831,1870,1878,1908,1916,1947,1955,1993,2001,2032,2038,2162,2168,2345,2350,2356,2361,2759,2765,2770,2793,2798,2804,2817,2972,2978,3005,3011,3092],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"query-aws-s3-system-tables",[48],{"type":49,"value":50},"text","Query AWS S3 System Tables",{"type":43,"tag":52,"props":53,"children":55},"h2",{"id":54},"overview",[56],{"type":49,"value":57},"Overview",{"type":43,"tag":59,"props":60,"children":61},"p",{},[62,68,70,79],{"type":43,"tag":63,"props":64,"children":65},"strong",{},[66],{"type":49,"value":67},"Works best with",{"type":49,"value":69}," the ",{"type":43,"tag":71,"props":72,"children":76},"a",{"href":73,"rel":74},"https:\u002F\u002Fdocs.aws.amazon.com\u002Fagent-toolkit\u002Flatest\u002Fuserguide\u002Fgetting-started-aws-mcp-server.html",[75],"nofollow",[77],{"type":49,"value":78},"AWS MCP server",{"type":49,"value":80}," for sandboxed execution and audit logging. 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Triggers on: \"connect to API\", \"add gateway\", \"connect to MCP server\", \"Lambda tools\", \"OpenAPI\", \"gateway target\", \"Cedar policy\", \"restrict tools\", \"policy engine\", \"gateway auth error\", \"store API key\", \"outbound credential\", \"env var API key\", \"API key None after deploy\", \"credential not available after deploy\", \"should this be a gateway target\", \"give my agent tools\", \"add tools to agent\". Not for inbound auth (who can call your agent) — use agents-harden. Not for debugging agent behavior — use agents-debug. Not for VPC networking errors (agent can't reach APIs due to VPC) — use agents-build. Not for creating or hosting a new MCP server project — use agents-get-started.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3123,3124,3127,3130],{"name":3107,"slug":3108,"type":15},{"name":3125,"slug":3126,"type":15},"API Development","api-development",{"name":3128,"slug":3129,"type":15},"Authentication","authentication",{"name":23,"slug":8,"type":15},"2026-07-16T06:00:38.866147",{"slug":3133,"name":3133,"fn":3134,"description":3135,"org":3136,"tags":3137,"stars":24,"repoUrl":25,"updatedAt":3146},"agents-debug","debug agent and environment issues","Use when your agent or environment is broken — wrong answers, errors, timeouts, tool failures, or CLI issues. Reads traces and logs to diagnose root causes. Also checks prerequisites when the CLI itself isn't working. Triggers on: \"agent not working\", \"wrong answer\", \"agent error\", \"tool call failing\", \"debug agent\", \"check logs\", \"read traces\", \"broken\", \"500 error\", \"424 error\", \"model access denied\", \"command not found\", \"stuck in DELETING\", \"maxVms exceeded\", \"cold start diagnosis\", \"cold start slow\", \"agentcore create error\", \"create failed\", \"exit code 7\", \"connection refused local dev\". Not for deploy failures — use agents-deploy. Not for performance tuning without errors — use agents-optimize. Not for VPC configuration — use agents-build. Not for observability setup or missing logs — use agents-optimize.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3138,3139,3140,3143],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3141,"slug":3142,"type":15},"Debugging","debugging",{"name":3144,"slug":3145,"type":15},"Observability","observability","2026-07-16T06:00:44.679093",{"slug":3148,"name":3148,"fn":3149,"description":3150,"org":3151,"tags":3152,"stars":24,"repoUrl":25,"updatedAt":3161},"agents-deploy","deploy AI agents to AWS","Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK\u002FIAM\u002Fquota error diagnosis, version management, rollback, and canary deployments. Triggers on: \"deploy my agent\", \"agentcore deploy\", \"deploy failed\", \"CDK error\", \"rollback\", \"canary deploy\", \"pin version\", \"redeploy\", \"deploy stuck\". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3153,3154,3155,3158],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3156,"slug":3157,"type":15},"CI\u002FCD","ci-cd",{"name":3159,"slug":3160,"type":15},"Deployment","deployment","2026-07-12T08:42:55.059577",{"slug":3163,"name":3163,"fn":3164,"description":3165,"org":3166,"tags":3167,"stars":24,"repoUrl":25,"updatedAt":3171},"agents-get-started","scaffold and deploy new agent projects","Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: \"build an agent\", \"create an agent\", \"get started\", \"new project\", \"agentcore create\", \"which framework\", \"Strands vs LangGraph\", \"hello world agent\", \"first agent\", \"create MCP server\", \"host MCP server\", \"agentcore dev\", \"dev server\", \"what port\", \"local development\". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3168,3169,3170],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3159,"slug":3160,"type":15},"2026-07-12T08:42:51.963247",{"slug":3173,"name":3173,"fn":3174,"description":3175,"org":3176,"tags":3177,"stars":24,"repoUrl":25,"updatedAt":3186},"agents-harden","harden agents for production","Use when preparing your agent for production — IAM scoping, inbound auth (JWT, SigV4), secrets management, cold start optimization, session lifecycle, rate limiting, input validation, and quota guidance. Triggers on: \"production checklist\", \"harden agent\", \"production ready\", \"secure agent\", \"inbound auth\", \"going live\", \"cold start optimization\", \"session lifecycle\", \"StopRuntimeSession\", \"quota\", \"throttling\", \"maxVms\", \"rate limit\", \"security audit of outbound API calls\", \"gateway target audit for production\", \"restrict who can call\", \"lock down endpoint\", \"only our app can call\". Not for Cedar tool-restriction policies — use agents-connect. Not for quality measurement — use agents-optimize. Not for outbound credential storage or API key wiring — use agents-connect. Not for A2A agent-to-agent auth — use agents-build. Cold start observation and diagnosis (not optimization) routes to agents-debug.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3178,3179,3180,3183],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3181,"slug":3182,"type":15},"Best Practices","best-practices",{"name":3184,"slug":3185,"type":15},"Security","security","2026-07-16T06:00:42.174705",{"slug":3188,"name":3188,"fn":3189,"description":3190,"org":3191,"tags":3192,"stars":24,"repoUrl":25,"updatedAt":3202},"agents-optimize","optimize agent quality and performance","Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI\u002FCD quality gates, observability, or cost optimization. Triggers on: \"evaluate my agent\", \"add evaluator\", \"measure quality\", \"quality gate\", \"run evals\", \"agent too slow\", \"why is it slow\", \"reduce latency\", \"set up observability\", \"CloudWatch dashboard\", \"how much does my agent cost\", \"cost optimization\", \"logs not showing up\", \"logs missing\", \"spans not found\", \"eval failing\", \"eval error\", \"dev traces\", \"local traces\", \"agentcore dev traces\", \"traces to CloudWatch\". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3193,3194,3195,3198,3199],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3196,"slug":3197,"type":15},"Evals","evals",{"name":3144,"slug":3145,"type":15},{"name":3200,"slug":3201,"type":15},"Performance","performance","2026-07-12T08:42:56.488105",114,{"items":3205,"total":3322},[3206,3213,3220,3227,3234,3240,3247,3255,3272,3285,3297,3312],{"slug":3101,"name":3101,"fn":3102,"description":3103,"org":3207,"tags":3208,"stars":24,"repoUrl":25,"updatedAt":3116},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3209,3210,3211,3212],{"name":3107,"slug":3108,"type":15},{"name":3110,"slug":3111,"type":15},{"name":23,"slug":8,"type":15},{"name":3114,"slug":3115,"type":15},{"slug":3118,"name":3118,"fn":3119,"description":3120,"org":3214,"tags":3215,"stars":24,"repoUrl":25,"updatedAt":3131},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3216,3217,3218,3219],{"name":3107,"slug":3108,"type":15},{"name":3125,"slug":3126,"type":15},{"name":3128,"slug":3129,"type":15},{"name":23,"slug":8,"type":15},{"slug":3133,"name":3133,"fn":3134,"description":3135,"org":3221,"tags":3222,"stars":24,"repoUrl":25,"updatedAt":3146},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3223,3224,3225,3226],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3141,"slug":3142,"type":15},{"name":3144,"slug":3145,"type":15},{"slug":3148,"name":3148,"fn":3149,"description":3150,"org":3228,"tags":3229,"stars":24,"repoUrl":25,"updatedAt":3161},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3230,3231,3232,3233],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3156,"slug":3157,"type":15},{"name":3159,"slug":3160,"type":15},{"slug":3163,"name":3163,"fn":3164,"description":3165,"org":3235,"tags":3236,"stars":24,"repoUrl":25,"updatedAt":3171},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3237,3238,3239],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3159,"slug":3160,"type":15},{"slug":3173,"name":3173,"fn":3174,"description":3175,"org":3241,"tags":3242,"stars":24,"repoUrl":25,"updatedAt":3186},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3243,3244,3245,3246],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3181,"slug":3182,"type":15},{"name":3184,"slug":3185,"type":15},{"slug":3188,"name":3188,"fn":3189,"description":3190,"org":3248,"tags":3249,"stars":24,"repoUrl":25,"updatedAt":3202},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3250,3251,3252,3253,3254],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3196,"slug":3197,"type":15},{"name":3144,"slug":3145,"type":15},{"name":3200,"slug":3201,"type":15},{"slug":3256,"name":3256,"fn":3257,"description":3258,"org":3259,"tags":3260,"stars":24,"repoUrl":25,"updatedAt":3271},"amazon-aurora-mysql","manage Amazon Aurora MySQL clusters","Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I\u002FO-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3261,3262,3265,3268],{"name":23,"slug":8,"type":15},{"name":3263,"slug":3264,"type":15},"Database","database",{"name":3266,"slug":3267,"type":15},"MySQL","mysql",{"name":3269,"slug":3270,"type":15},"Serverless","serverless","2026-07-12T08:43:13.27939",{"slug":3273,"name":3273,"fn":3274,"description":3275,"org":3276,"tags":3277,"stars":24,"repoUrl":25,"updatedAt":3284},"amazon-aurora-postgresql","configure Amazon Aurora PostgreSQL clusters","Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I\u002FO-Optimized storage, commitment pricing, or PostgreSQL upgrade planning. For Aurora MySQL, use amazon-aurora-mysql instead. Contains safety guardrails, express-first routing, and response templates that override defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3278,3279,3280,3283],{"name":23,"slug":8,"type":15},{"name":3263,"slug":3264,"type":15},{"name":3281,"slug":3282,"type":15},"PostgreSQL","postgresql",{"name":3269,"slug":3270,"type":15},"2026-07-16T06:00:34.789624",{"slug":3286,"name":3286,"fn":3287,"description":3288,"org":3289,"tags":3290,"stars":24,"repoUrl":25,"updatedAt":3296},"amazon-bedrock","build generative AI apps with Amazon Bedrock","Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating\u002Fporting\u002Fconverting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. Also covers AgentCore Payments setup (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, 402 Payment Required, pay for content, paid endpoint, agent payments). NOT for custom model training, Rekognition, or Comprehend.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3291,3292,3293],{"name":3107,"slug":3108,"type":15},{"name":23,"slug":8,"type":15},{"name":3294,"slug":3295,"type":15},"LLM","llm","2026-07-25T05:30:35.20899",{"slug":3298,"name":3298,"fn":3299,"description":3300,"org":3301,"tags":3302,"stars":24,"repoUrl":25,"updatedAt":3311},"amazon-documentdb","manage Amazon DocumentDB clusters","Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS\u002FVPC\u002Fdriver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0→5.0→8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3303,3304,3305,3308],{"name":23,"slug":8,"type":15},{"name":3263,"slug":3264,"type":15},{"name":3306,"slug":3307,"type":15},"MongoDB","mongodb",{"name":3309,"slug":3310,"type":15},"NoSQL","nosql","2026-07-12T08:43:00.455878",{"slug":3313,"name":3313,"fn":3314,"description":3315,"org":3316,"tags":3317,"stars":24,"repoUrl":25,"updatedAt":3321},"amazon-dynamodb","design and debug DynamoDB data layers","Designs, reviews, and debugs DynamoDB data layers from design axioms — enumerates access patterns, chooses partition\u002Fsort keys and GSIs, decides single-table vs. multi-table, configures Streams, Global Tables, TTL, and zero-ETL integrations to OpenSearch\u002FRedshift\u002FSageMaker Lakehouse, and produces a defensible data-layer design with a monthly cost estimate and optional live validation. Applies whenever a user is designing, reviewing, or refactoring anything backed by DynamoDB — schemas, access patterns, GSIs, single- vs. multi-table choices, Streams consumers, transactional outboxes, Global Tables, zero-ETL pipelines — even when they don't say \"axioms\" or \"design review.\" Also applies when debugging hot partitions, throttling, unbounded Scans, LWW conflicts, or surprise bills on DynamoDB workloads.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3318,3319,3320],{"name":23,"slug":8,"type":15},{"name":3263,"slug":3264,"type":15},{"name":3309,"slug":3310,"type":15},"2026-07-16T06:00:37.690386",115]