[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-aws-connecting-to-data-source":3,"mdc--8xkrbn-key":35,"related-repo-aws-connecting-to-data-source":1257,"related-org-aws-connecting-to-data-source":1363},{"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},"connecting-to-data-source","connect AWS Glue to data sources","Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS\u002FRedshift candidates, registers credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers on: connect to database, set up Glue connection, register data source, connect to Snowflake\u002FBigQuery\u002FRDS, connection timeout, test connection, troubleshoot connection. Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use creating-data-lake-table), queries (use querying-data-lake), catalog exploration (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).",{"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},"Data Engineering","data-engineering","tag",{"name":17,"slug":18,"type":15},"Integrations","integrations",{"name":20,"slug":21,"type":15},"Database","database",{"name":23,"slug":8,"type":15},"AWS",1822,"https:\u002F\u002Fgithub.com\u002Faws\u002Fagent-toolkit-for-aws","2026-07-12T08:43:26.001514",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\u002Fplugins\u002Faws-data-analytics\u002Fskills\u002Fconnecting-to-data-source","---\nname: connecting-to-data-source\ndescription: >-\n  Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server,\n  PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints\n  from user, discovers existing connections and RDS\u002FRedshift candidates, registers\n  credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers\n  on: connect to database, set up Glue connection, register data source, connect to\n  Snowflake\u002FBigQuery\u002FRDS, connection timeout, test connection, troubleshoot connection.\n  Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use\n  creating-data-lake-table), queries (use querying-data-lake), catalog exploration\n  (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).\nversion: 1\nargument-hint: '[source-type|connection-name|hostname]'\n---\n\n# Connect to Data Source\n\nRegister an external data source with AWS Glue so downstream skills (ingesting-into-data-lake) can move data from it. A Glue connection stores the network config, driver, and credential reference for one source. Create once per source, reuse across jobs.\n\n## Philosophy\n\n**A connection is a named pipe, not a pipeline.** This skill produces a tested, reusable Glue connection. It does not move data.\n\n## Common Tasks\n\nYou MUST execute commands using AWS MCP server tools when connected -- they provide validation, sandboxed execution, and audit logging. Fall back to AWS CLI only if MCP is unavailable. You MUST explain each step before executing.\n\n## Workflow\n\n### 1. Verify Dependencies and Context\n\n- You MUST check whether AWS MCP tools or AWS CLI are available and inform the user if missing\n- You MUST confirm target AWS region and verify credentials with `aws sts get-caller-identity`\n\n### 2. Classify the Source\n\nAsk the user which source type they want to connect to, or infer from hints:\n\n| User says... | Source type | Connection type | Reference |\n|---|---|---|---|\n| \"Oracle\", \"SQL Server\", \"Postgres\", \"MySQL\", \"RDS \\\u003Cengine\\>\" | JDBC database | `JDBC` | [jdbc-setup.md](references\u002Fjdbc-setup.md) |\n| \"Redshift\", \"my cluster\", \"my data warehouse on AWS\" | Redshift | `JDBC` | [jdbc-setup.md](references\u002Fjdbc-setup.md) (Redshift section) |\n| \"Snowflake\" | Snowflake | `SNOWFLAKE` | [snowflake-setup.md](references\u002Fsnowflake-setup.md) |\n| \"BigQuery\", \"Google analytics warehouse\" | BigQuery | `BIGQUERY` | [bigquery-setup.md](references\u002Fbigquery-setup.md) |\n\nIf the user names DynamoDB or a local file, stop and tell them: DynamoDB is read directly by Glue without a connection, and local files belong in the ingesting-into-data-lake skill's local-upload workflow.\n\n### 3. Gather Connection Hints from the User\n\nYou MUST ask for hints the user can provide -- do not guess.\n\n**For all sources:**\n\n- Desired connection name (lowercase, hyphens: `oracle-prod-sales`, `snowflake-analytics`)\n- Existing Secrets Manager secret, or create one\n- Is source reachable from a Glue VPC (same, peered, VPN, Direct Connect)\n\n**JDBC:** hostname\u002Fendpoint, port, database, whether RDS\u002FAurora\u002Fself-managed, IAM DB auth enabled (Aurora\u002FRDS MySQL\u002FPostgres), SSL required.\n\n**Snowflake:** account identifier, warehouse, role, default database, auth (password, key-pair, OAuth).\n\n**BigQuery:** GCP project ID, location, whether service account JSON is provisioned.\n\n### 4. Discover Existing Connections and Candidate Sources\n\nCheck what exists before creating.\n\n**Existing Glue connections:**\n\n```bash\naws glue get-connections --filter ConnectionType=\u003CTYPE> --region \u003CREGION>\n```\n\nIf a suitable one exists, confirm and skip to Step 7.\n\n**Candidate sources in account** (JDBC\u002FRedshift only):\n\n- RDS: `aws rds describe-db-instances`\n- Aurora: `aws rds describe-db-clusters`\n- Redshift: `aws redshift describe-clusters`\n\nPresent candidates to user; let them pick. See [discovery.md](references\u002Fdiscovery.md).\n\n### 5. Register Credentials\n\nYou MUST encourage AWS Secrets Manager over plaintext passwords. You SHOULD prefer IAM database authentication where supported (Aurora\u002FRDS MySQL and PostgreSQL, Redshift). See [credential-security.md](references\u002Fcredential-security.md).\n\n- You MUST confirm with user before creating a new Secrets Manager secret\n- You MUST NOT write plaintext credentials into chat or logs\n- For IAM DB auth, no secret is needed\n\n### 6. Create the Glue Connection\n\nFollow the source-specific reference for connection properties:\n\n```bash\naws glue create-connection --connection-input '\u003CJSON>' --region \u003CREGION>\n```\n\nPrivate sources require `PhysicalConnectionRequirements` (SubnetId, SecurityGroupIdList, AvailabilityZone). See [network-setup.md](references\u002Fnetwork-setup.md).\n\n### 7. Test the Connection\n\nYou MUST test before handing off. Testing is two-phase: a quick API check, then an engine-level verification.\n\n#### Phase A: Glue TestConnection (network and credential sanity check)\n\n```bash\naws glue test-connection --connection-name \u003CNAME> --region \u003CREGION>\n```\n\nThis validates that Glue can reach the source and authenticate. It does NOT prove the connection works end-to-end with the query engine the user plans to use.\n\n#### Phase B: Engine-level verification\n\nAfter TestConnection passes, verify the connection works with the user's intended engine by running a minimal query through it:\n\n- **Glue ETL (default):** Run a smoke-test Glue job that reads one row via the connection. See [troubleshooting.md](references\u002Ftroubleshooting.md).\n- **Athena:** If the user plans to query via Athena with a federated connector, run a `SELECT 1` through the Athena connection to confirm the Lambda-based connector can reach the source.\n- **Glue Crawler:** If the user plans to crawl the source, run a test crawl on a single table.\n\nPhase B catches issues that TestConnection misses: driver compatibility at job runtime, catalog configuration, Spark-level serialization, and engine-specific auth flows (e.g., Snowflake SNOWFLAKE type works in ETL but not via JDBC crawlers).\n\nOn success in both phases, tell user the connection name is ready for `ingesting-into-data-lake`. On failure in either phase, Step 8.\n\n### 8. Troubleshoot (only if test failed)\n\nDiagnose in order: network, credentials, driver. See [troubleshooting.md](references\u002Ftroubleshooting.md).\n\n**Constraints:**\n\n- You MUST check VPC routing, security groups, and S3 VPC endpoint before blaming credentials\n- You MUST verify Glue role can read the Secrets Manager secret\n- You MUST NOT rotate credentials without user confirmation\n\n## Argument Routing\n\n- No args: Walk through Steps 1-7 interactively\n- Source type keyword (e.g., `snowflake`, `oracle`): Skip to Step 2 with the type prefilled\n- Existing connection name: Skip to Step 7 (test) then Step 8 if failing\n- Hostname or RDS endpoint: Skip to Step 4 with the candidate prefilled\n\n## Gotchas\n\n- Glue's `SNOWFLAKE` connection type is distinct from `JDBC` configured for Snowflake. You MUST use `SNOWFLAKE` for Spark ETL jobs; do not use JDBC.\n- Connection names are immutable. Choose carefully.\n- `PhysicalConnectionRequirements.AvailabilityZone` MUST match the subnet's AZ or the connection fails at job runtime, not creation time.\n- IAM database authentication tokens expire in 15 minutes. The Glue job generates a fresh token on each connection; do not cache.\n- An S3 VPC gateway endpoint MUST exist in the VPC used by private-source connections. Without it, Glue jobs cannot read their scripts or write results to S3.\n\n## Troubleshooting\n\n| Error | Likely cause | Fix |\n|---|---|---|\n| `Connect timed out` | VPC routing, SG rule, or NAT gateway missing | See [troubleshooting.md](references\u002Ftroubleshooting.md) |\n| `Access denied for user` \u002F `ORA-01017` | Credentials wrong, Secrets Manager access missing, or IAM DB auth misconfigured | See [troubleshooting.md](references\u002Ftroubleshooting.md) |\n| `No suitable driver found` | Custom driver JAR not set or wrong class name | See [troubleshooting.md](references\u002Ftroubleshooting.md) |\n| `SSL handshake failed` | `JDBC_ENFORCE_SSL` mismatch between Glue and source | See [troubleshooting.md](references\u002Ftroubleshooting.md) |\n| `UnableToFindVpcEndpoint` | S3 VPC endpoint missing | Create S3 gateway endpoint in the connection's VPC |\n\n## References\n\n- [jdbc-setup.md](references\u002Fjdbc-setup.md) -- Oracle, SQL Server, PostgreSQL, MySQL, RDS, Redshift\n- [snowflake-setup.md](references\u002Fsnowflake-setup.md) -- Glue `SNOWFLAKE` type, auth modes\n- [bigquery-setup.md](references\u002Fbigquery-setup.md) -- Glue `BIGQUERY` type, GCP service accounts\n- [discovery.md](references\u002Fdiscovery.md) -- Finding existing connections and candidate sources\n- [credential-security.md](references\u002Fcredential-security.md) -- Secrets Manager and IAM DB auth\n- [network-setup.md](references\u002Fnetwork-setup.md) -- VPC, subnets, security groups, endpoints\n- [troubleshooting.md](references\u002Ftroubleshooting.md) -- Connection errors and diagnostic flow\n",{"data":36,"body":39},{"name":4,"description":6,"version":37,"argument-hint":38},1,"[source-type|connection-name|hostname]",{"type":40,"children":41},"root",[42,51,57,64,75,81,86,92,99,121,127,132,294,299,305,310,318,352,362,372,382,388,393,401,490,495,505,541,554,560,572,590,596,601,664,684,690,695,702,767,772,778,783,831,836,849,855,865,873,891,897,935,941,996,1002,1166,1172,1251],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"connect-to-data-source",[48],{"type":49,"value":50},"text","Connect to Data Source",{"type":43,"tag":52,"props":53,"children":54},"p",{},[55],{"type":49,"value":56},"Register an external data source with AWS Glue so downstream skills (ingesting-into-data-lake) can move data from it. 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modes",{"type":43,"tag":104,"props":1201,"children":1202},{},[1203,1207,1208,1213],{"type":43,"tag":196,"props":1204,"children":1205},{"href":290},[1206],{"type":49,"value":293},{"type":49,"value":1192},{"type":43,"tag":115,"props":1209,"children":1211},{"className":1210},[],[1212],{"type":49,"value":284},{"type":49,"value":1214}," type, GCP service accounts",{"type":43,"tag":104,"props":1216,"children":1217},{},[1218,1222],{"type":43,"tag":196,"props":1219,"children":1220},{"href":548},[1221],{"type":49,"value":551},{"type":49,"value":1223}," -- Finding existing connections and candidate sources",{"type":43,"tag":104,"props":1225,"children":1226},{},[1227,1231],{"type":43,"tag":196,"props":1228,"children":1229},{"href":567},[1230],{"type":49,"value":570},{"type":49,"value":1232}," -- Secrets Manager and IAM DB auth",{"type":43,"tag":104,"props":1234,"children":1235},{},[1236,1240],{"type":43,"tag":196,"props":1237,"children":1238},{"href":679},[1239],{"type":49,"value":682},{"type":49,"value":1241}," -- VPC, subnets, security groups, endpoints",{"type":43,"tag":104,"props":1243,"children":1244},{},[1245,1249],{"type":43,"tag":196,"props":1246,"children":1247},{"href":798},[1248],{"type":49,"value":801},{"type":49,"value":1250}," -- Connection errors and diagnostic flow",{"type":43,"tag":1252,"props":1253,"children":1254},"style",{},[1255],{"type":49,"value":1256},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":1258,"total":1362},[1259,1276,1291,1306,1321,1331,1346],{"slug":1260,"name":1260,"fn":1261,"description":1262,"org":1263,"tags":1264,"stars":24,"repoUrl":25,"updatedAt":1275},"agents-build","add capabilities to existing agent projects","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\", \"pay for x402 content\", \"402 Payment Required\", \"microtransactions\", \"paid API or tool\". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI\u002Fdev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1265,1268,1271,1272],{"name":1266,"slug":1267,"type":15},"Agents","agents",{"name":1269,"slug":1270,"type":15},"Automation","automation",{"name":23,"slug":8,"type":15},{"name":1273,"slug":1274,"type":15},"Engineering","engineering","2026-07-12T08:42:53.812877",{"slug":1277,"name":1277,"fn":1278,"description":1279,"org":1280,"tags":1281,"stars":24,"repoUrl":25,"updatedAt":1290},"agents-connect","connect agents to external services","Use when connecting your agent to external APIs, tools, or services via Gateway, or restricting tool access with Cedar policies. Handles gateway setup, target types, outbound auth (OAuth, API key, IAM), credentials, and Cedar policy authoring. 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},[1282,1283,1286,1289],{"name":1266,"slug":1267,"type":15},{"name":1284,"slug":1285,"type":15},"API Development","api-development",{"name":1287,"slug":1288,"type":15},"Authentication","authentication",{"name":23,"slug":8,"type":15},"2026-07-16T06:00:38.866147",{"slug":1292,"name":1292,"fn":1293,"description":1294,"org":1295,"tags":1296,"stars":24,"repoUrl":25,"updatedAt":1305},"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},[1297,1298,1299,1302],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1300,"slug":1301,"type":15},"Debugging","debugging",{"name":1303,"slug":1304,"type":15},"Observability","observability","2026-07-16T06:00:44.679093",{"slug":1307,"name":1307,"fn":1308,"description":1309,"org":1310,"tags":1311,"stars":24,"repoUrl":25,"updatedAt":1320},"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},[1312,1313,1314,1317],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1315,"slug":1316,"type":15},"CI\u002FCD","ci-cd",{"name":1318,"slug":1319,"type":15},"Deployment","deployment","2026-07-12T08:42:55.059577",{"slug":1322,"name":1322,"fn":1323,"description":1324,"org":1325,"tags":1326,"stars":24,"repoUrl":25,"updatedAt":1330},"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},[1327,1328,1329],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1318,"slug":1319,"type":15},"2026-07-12T08:42:51.963247",{"slug":1332,"name":1332,"fn":1333,"description":1334,"org":1335,"tags":1336,"stars":24,"repoUrl":25,"updatedAt":1345},"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},[1337,1338,1339,1342],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1340,"slug":1341,"type":15},"Best Practices","best-practices",{"name":1343,"slug":1344,"type":15},"Security","security","2026-07-16T06:00:42.174705",{"slug":1347,"name":1347,"fn":1348,"description":1349,"org":1350,"tags":1351,"stars":24,"repoUrl":25,"updatedAt":1361},"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},[1352,1353,1354,1357,1358],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1355,"slug":1356,"type":15},"Evals","evals",{"name":1303,"slug":1304,"type":15},{"name":1359,"slug":1360,"type":15},"Performance","performance","2026-07-12T08:42:56.488105",114,{"items":1364,"total":1479},[1365,1372,1379,1386,1393,1399,1406,1414,1429,1442,1454,1469],{"slug":1260,"name":1260,"fn":1261,"description":1262,"org":1366,"tags":1367,"stars":24,"repoUrl":25,"updatedAt":1275},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1368,1369,1370,1371],{"name":1266,"slug":1267,"type":15},{"name":1269,"slug":1270,"type":15},{"name":23,"slug":8,"type":15},{"name":1273,"slug":1274,"type":15},{"slug":1277,"name":1277,"fn":1278,"description":1279,"org":1373,"tags":1374,"stars":24,"repoUrl":25,"updatedAt":1290},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1375,1376,1377,1378],{"name":1266,"slug":1267,"type":15},{"name":1284,"slug":1285,"type":15},{"name":1287,"slug":1288,"type":15},{"name":23,"slug":8,"type":15},{"slug":1292,"name":1292,"fn":1293,"description":1294,"org":1380,"tags":1381,"stars":24,"repoUrl":25,"updatedAt":1305},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1382,1383,1384,1385],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1300,"slug":1301,"type":15},{"name":1303,"slug":1304,"type":15},{"slug":1307,"name":1307,"fn":1308,"description":1309,"org":1387,"tags":1388,"stars":24,"repoUrl":25,"updatedAt":1320},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1389,1390,1391,1392],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1315,"slug":1316,"type":15},{"name":1318,"slug":1319,"type":15},{"slug":1322,"name":1322,"fn":1323,"description":1324,"org":1394,"tags":1395,"stars":24,"repoUrl":25,"updatedAt":1330},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1396,1397,1398],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1318,"slug":1319,"type":15},{"slug":1332,"name":1332,"fn":1333,"description":1334,"org":1400,"tags":1401,"stars":24,"repoUrl":25,"updatedAt":1345},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1402,1403,1404,1405],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1340,"slug":1341,"type":15},{"name":1343,"slug":1344,"type":15},{"slug":1347,"name":1347,"fn":1348,"description":1349,"org":1407,"tags":1408,"stars":24,"repoUrl":25,"updatedAt":1361},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1409,1410,1411,1412,1413],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1355,"slug":1356,"type":15},{"name":1303,"slug":1304,"type":15},{"name":1359,"slug":1360,"type":15},{"slug":1415,"name":1415,"fn":1416,"description":1417,"org":1418,"tags":1419,"stars":24,"repoUrl":25,"updatedAt":1428},"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},[1420,1421,1422,1425],{"name":23,"slug":8,"type":15},{"name":20,"slug":21,"type":15},{"name":1423,"slug":1424,"type":15},"MySQL","mysql",{"name":1426,"slug":1427,"type":15},"Serverless","serverless","2026-07-12T08:43:13.27939",{"slug":1430,"name":1430,"fn":1431,"description":1432,"org":1433,"tags":1434,"stars":24,"repoUrl":25,"updatedAt":1441},"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},[1435,1436,1437,1440],{"name":23,"slug":8,"type":15},{"name":20,"slug":21,"type":15},{"name":1438,"slug":1439,"type":15},"PostgreSQL","postgresql",{"name":1426,"slug":1427,"type":15},"2026-07-16T06:00:34.789624",{"slug":1443,"name":1443,"fn":1444,"description":1445,"org":1446,"tags":1447,"stars":24,"repoUrl":25,"updatedAt":1453},"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},[1448,1449,1450],{"name":1266,"slug":1267,"type":15},{"name":23,"slug":8,"type":15},{"name":1451,"slug":1452,"type":15},"LLM","llm","2026-07-25T05:30:35.20899",{"slug":1455,"name":1455,"fn":1456,"description":1457,"org":1458,"tags":1459,"stars":24,"repoUrl":25,"updatedAt":1468},"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},[1460,1461,1462,1465],{"name":23,"slug":8,"type":15},{"name":20,"slug":21,"type":15},{"name":1463,"slug":1464,"type":15},"MongoDB","mongodb",{"name":1466,"slug":1467,"type":15},"NoSQL","nosql","2026-07-12T08:43:00.455878",{"slug":1470,"name":1470,"fn":1471,"description":1472,"org":1473,"tags":1474,"stars":24,"repoUrl":25,"updatedAt":1478},"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},[1475,1476,1477],{"name":23,"slug":8,"type":15},{"name":20,"slug":21,"type":15},{"name":1466,"slug":1467,"type":15},"2026-07-16T06:00:37.690386",115]