[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-aws-amazon-opensearch-service":3,"mdc-kr6qrx-key":35,"related-repo-aws-amazon-opensearch-service":755,"related-org-aws-amazon-opensearch-service":861},{"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},"amazon-opensearch-service","migrate and provision Amazon OpenSearch Service","Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr\u002FES\u002Fself-managed OpenSearch into AOS\u002FAOSS, schema\u002Fquery translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector \u002F semantic \u002F hybrid \u002F RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk\u002FDatadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector \u002F k-NN \u002F semantic \u002F hybrid \u002F neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk\u002FDatadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.",{"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},"Migration","migration","tag",{"name":17,"slug":18,"type":15},"Search","search",{"name":20,"slug":21,"type":15},"Infrastructure","infrastructure",{"name":23,"slug":8,"type":15},"AWS",1822,"https:\u002F\u002Fgithub.com\u002Faws\u002Fagent-toolkit-for-aws","2026-07-12T08:43:20.10591",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\u002Famazon-opensearch-service","---\nname: amazon-opensearch-service\ndescription: Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr\u002FES\u002Fself-managed OpenSearch into AOS\u002FAOSS, schema\u002Fquery translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector \u002F semantic \u002F hybrid \u002F RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk\u002FDatadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector \u002F k-NN \u002F semantic \u002F hybrid \u002F neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk\u002FDatadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.\nversion: 1\n---\n\n# Amazon OpenSearch Service — the unified skill\n\nThis skill answers anything about Amazon OpenSearch Service or Serverless across five capabilities. **Step 0 below routes the question to ONE capability** and points at that capability's entry-point reference. Everything else — when to dispatch, sub-references, capability-specific facts, cross-capability links — lives in the entry-point reference for that capability.\n\n> **AWS MCP server is recommended, not required.** Capability references show standard AWS CLI commands as the primary syntax (e.g., `aws opensearch describe-domain`, `aws opensearchserverless create-collection`). Where the AWS MCP server is available, its `call_aws` tool offers a streamlined alternative — but every operation in this skill MUST work via the AWS CLI alone. Data-plane HTTP calls against AOS \u002F AOSS use `awscurl` for SigV4-signed requests; this works in both contexts.\n\n## Step 0: detect the capability — first thing you do\n\nPick **one** of the five capabilities below. State the detected capability in your first sentence (e.g., *\"Detected capability: SEARCH — semantic search setup with Bedrock embeddings.\"*). Then load the entry-point reference; that file describes when to dispatch, indexes the rest of the capability's files, and routes you to the next step.\n\n| Capability | Entry-point reference |\n|---|---|\n| **migration** — Solr \u002F Elasticsearch \u002F self-managed OpenSearch into AOS or AOSS. Schema\u002Fquery translation, sizing, cutover. | [`references\u002Fassessment-workflow.md`](references\u002Fassessment-workflow.md) |\n| **provisioning** — Provisioning and managing AOS domains and AOSS collections. Lifecycle, upgrades, storage tiers, FGAC, monitoring. | [`references\u002Fprovisioning-reference.md`](references\u002Fprovisioning-reference.md) |\n| **search** — Vector \u002F semantic \u002F hybrid \u002F sparse \u002F dense \u002F RAG retrieval. Bedrock connectors, FAISS HNSW vs Lucene. | [`references\u002Fsearch-semantic-search-guide.md`](references\u002Fsearch-semantic-search-guide.md) |\n| **log-analytics** — Log search, observability, PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards. Splunk\u002FDatadog\u002FELK alternatives. | [`references\u002Flog-analytics-guide.md`](references\u002Flog-analytics-guide.md) |\n| **trace-analytics** — Distributed traces with OpenTelemetry. Span queries, service maps, Data Prepper. | [`references\u002Ftrace-analytics-trace-queries.md`](references\u002Ftrace-analytics-trace-queries.md) |\n\nIf a prompt spans capabilities (e.g., *\"migrate from Solr AND set up RAG on the new domain\"*), pick the dominant capability for the response and close with a one-line handoff to the other capability's entry-point ref.\n\n## Universal rules (apply to ALL capabilities)\n\nThese rules apply to every response, regardless of capability. Capability-specific rules (sizing math, shape detection, Migration Assistant for Amazon OpenSearch Service capability matrix, k-NN engine selection) live in the entry-point references, not here.\n\n- **Report header (every multi-section response).** Begin every multi-section response with a single fenced metadata block: `> Generated: \u003CISO 8601 timestamp> | Skill: amazon-opensearch-service v\u003CN>`. Get the time by calling the `current_time` tool (returns ISO 8601 in UTC). Read the skill version from this file's frontmatter `version:` field. For one-line answers (terse FOCUSED_OPERATIONAL replies, anti-pattern refusals) the header is optional; for any multi-section deliverable it is REQUIRED. Place it immediately after the report title and before the first `##` heading.\n- **No dollar estimates** (HARD CONSTRAINT). Never produce `$X\u002Fmonth`, `~$1,500`, or any dollar figure. Route every cost question to \u003Chttps:\u002F\u002Fcalculator.aws> and stop. If a sub-reference contains dollar figures, treat them as informational context only and do NOT pass them through to the user.\n- **No credential leakage** (HARD CONSTRAINT). Never include master usernames, KMS key ARNs, VPC endpoint URLs, instance IPs, or account IDs in generated output.\n- **Pick one** for every A-vs-B decision. Name a primary recommendation in one line with a one-sentence reason. A *\"go with B if...\"* caveat is allowed AFTER the primary; never lead with conditional-only guidance.\n- **Source restatement.** The first 2–3 sentences must restate the source (engine + version + scale) when known, or restate the customer's question in concrete terms. The very first text the user sees must NOT be tool narration, meta-commentary, the report title, or simply restating the question verbatim.\n- **No marketing tone.** Do NOT use *\"seamless\"*, *\"robust\"*, *\"best-in-class\"*, *\"production-hardened\"*, *\"enterprise-grade\"*, *\"world-class\"*, *\"cleanly\"*, *\"elegant\"*. Do NOT stack 3+ vague hedges (*\"typically\"*, *\"generally\"*, *\"usually\"*, *\"in most cases\"*) in a single recommendation — be specific about when it does and does not apply.\n- **Cross-capability handoff.** When a user prompt spans capabilities (e.g., *\"migrate from Solr AND set up RAG on the new domain\"*), pick the dominant capability for the response, then close with a one-line handoff: *\"For \\\u003Cother capability\\>, see [`references\u002F\u003Cother-capability>-\u003Centry>.md`](...).\"*\n\n## Cross-cutting references (used across multiple capabilities)\n\nThese references are not capability-prefixed because they apply across capabilities. Capability entry-point references load them when relevant; SKILL.md never loads them directly.\n\n- [`references\u002Fsizing.md`](references\u002Fsizing.md) — sizing math, instance family details, OR1 trade-offs, watermarks, JVM heap rules.\n- [`references\u002Fvector-knn.md`](references\u002Fvector-knn.md) — k-NN engines, memory math, RAG ingestion patterns, ELSER alternatives.\n- [`references\u002Fobservability.md`](references\u002Fobservability.md) — log analytics patterns, ISM, UltraWarm\u002FCold tiering, Splunk\u002FDatadog migration playbooks.\n- [`references\u002Fsecurity.md`](references\u002Fsecurity.md) — FGAC, encryption, VPC patterns, audit logs, compliance posture.\n- [`references\u002Fpersonas.md`](references\u002Fpersonas.md) — communication style per persona.\n- [`references\u002Fassessment-gotchas.md`](references\u002Fassessment-gotchas.md) — production gotcha catalog (cite by number in Migration specifics or Risks\u002Fblockers tables; each gotcha carries a `Category:` tag that determines its lane).\n- [`references\u002Fassessment-knowledge-retrieval.md`](references\u002Fassessment-knowledge-retrieval.md) — topic → tool → URL recipe for batched verification.\n\nAssets (`assets\u002F`): report templates for FULL_ASSESSMENT renderings (Solr-source, ES-source, executive summary).\n\n## What this skill does NOT do\n\n- **Estimate dollar costs.** Pricing changes monthly and account-specific (RI, Savings Plan, EDP) discount math is outside this skill's reliable scope. Use \u003Chttps:\u002F\u002Fcalculator.aws>.\n- **Move data.** Use Migration Assistant for Amazon OpenSearch Service (Historical Data Migration for backfill, Live Traffic Migration for live cutover).\n- **Build embedding models.** Use Amazon Bedrock or SageMaker.\n- **Replace Splunk SPL or Datadog APM 1:1.** Some queries \u002F detectors \u002F dashboards need rewriting.\n- **Tune relevance for a specific catalog.** Use OpenSearch Benchmark `big5` workload + your own judgment list.\n",{"data":36,"body":38},{"name":4,"description":6,"version":37},1,{"type":39,"children":40},"root",[41,50,64,111,118,138,290,302,308,313,548,554,559,668,681,687],{"type":42,"tag":43,"props":44,"children":46},"element","h1",{"id":45},"amazon-opensearch-service-the-unified-skill",[47],{"type":48,"value":49},"text","Amazon OpenSearch Service — the unified skill",{"type":42,"tag":51,"props":52,"children":53},"p",{},[54,56,62],{"type":48,"value":55},"This skill answers anything about Amazon OpenSearch Service or Serverless across five capabilities. ",{"type":42,"tag":57,"props":58,"children":59},"strong",{},[60],{"type":48,"value":61},"Step 0 below routes the question to ONE capability",{"type":48,"value":63}," and points at that capability's entry-point reference. Everything else — when to dispatch, sub-references, capability-specific facts, cross-capability links — lives in the entry-point reference for that capability.",{"type":42,"tag":65,"props":66,"children":67},"blockquote",{},[68],{"type":42,"tag":51,"props":69,"children":70},{},[71,76,78,85,87,93,95,101,103,109],{"type":42,"tag":57,"props":72,"children":73},{},[74],{"type":48,"value":75},"AWS MCP server is recommended, not required.",{"type":48,"value":77}," Capability references show standard AWS CLI commands as the primary syntax (e.g., ",{"type":42,"tag":79,"props":80,"children":82},"code",{"className":81},[],[83],{"type":48,"value":84},"aws opensearch describe-domain",{"type":48,"value":86},", ",{"type":42,"tag":79,"props":88,"children":90},{"className":89},[],[91],{"type":48,"value":92},"aws opensearchserverless create-collection",{"type":48,"value":94},"). Where the AWS MCP server is available, its ",{"type":42,"tag":79,"props":96,"children":98},{"className":97},[],[99],{"type":48,"value":100},"call_aws",{"type":48,"value":102}," tool offers a streamlined alternative — but every operation in this skill MUST work via the AWS CLI alone. Data-plane HTTP calls against AOS \u002F AOSS use ",{"type":42,"tag":79,"props":104,"children":106},{"className":105},[],[107],{"type":48,"value":108},"awscurl",{"type":48,"value":110}," for SigV4-signed requests; this works in both contexts.",{"type":42,"tag":112,"props":113,"children":115},"h2",{"id":114},"step-0-detect-the-capability-first-thing-you-do",[116],{"type":48,"value":117},"Step 0: detect the capability — first thing you do",{"type":42,"tag":51,"props":119,"children":120},{},[121,123,128,130,136],{"type":48,"value":122},"Pick ",{"type":42,"tag":57,"props":124,"children":125},{},[126],{"type":48,"value":127},"one",{"type":48,"value":129}," of the five capabilities below. State the detected capability in your first sentence (e.g., ",{"type":42,"tag":131,"props":132,"children":133},"em",{},[134],{"type":48,"value":135},"\"Detected capability: SEARCH — semantic search setup with Bedrock embeddings.\"",{"type":48,"value":137},"). Then load the entry-point reference; that file describes when to dispatch, indexes the rest of the capability's files, and routes you to the next step.",{"type":42,"tag":139,"props":140,"children":141},"table",{},[142,161],{"type":42,"tag":143,"props":144,"children":145},"thead",{},[146],{"type":42,"tag":147,"props":148,"children":149},"tr",{},[150,156],{"type":42,"tag":151,"props":152,"children":153},"th",{},[154],{"type":48,"value":155},"Capability",{"type":42,"tag":151,"props":157,"children":158},{},[159],{"type":48,"value":160},"Entry-point reference",{"type":42,"tag":162,"props":163,"children":164},"tbody",{},[165,191,216,240,265],{"type":42,"tag":147,"props":166,"children":167},{},[168,178],{"type":42,"tag":169,"props":170,"children":171},"td",{},[172,176],{"type":42,"tag":57,"props":173,"children":174},{},[175],{"type":48,"value":14},{"type":48,"value":177}," — Solr \u002F Elasticsearch \u002F self-managed OpenSearch into AOS or AOSS. Schema\u002Fquery translation, sizing, cutover.",{"type":42,"tag":169,"props":179,"children":180},{},[181],{"type":42,"tag":182,"props":183,"children":185},"a",{"href":184},"references\u002Fassessment-workflow.md",[186],{"type":42,"tag":79,"props":187,"children":189},{"className":188},[],[190],{"type":48,"value":184},{"type":42,"tag":147,"props":192,"children":193},{},[194,204],{"type":42,"tag":169,"props":195,"children":196},{},[197,202],{"type":42,"tag":57,"props":198,"children":199},{},[200],{"type":48,"value":201},"provisioning",{"type":48,"value":203}," — Provisioning and managing AOS domains and AOSS collections. Lifecycle, upgrades, storage tiers, FGAC, monitoring.",{"type":42,"tag":169,"props":205,"children":206},{},[207],{"type":42,"tag":182,"props":208,"children":210},{"href":209},"references\u002Fprovisioning-reference.md",[211],{"type":42,"tag":79,"props":212,"children":214},{"className":213},[],[215],{"type":48,"value":209},{"type":42,"tag":147,"props":217,"children":218},{},[219,228],{"type":42,"tag":169,"props":220,"children":221},{},[222,226],{"type":42,"tag":57,"props":223,"children":224},{},[225],{"type":48,"value":18},{"type":48,"value":227}," — Vector \u002F semantic \u002F hybrid \u002F sparse \u002F dense \u002F RAG retrieval. Bedrock connectors, FAISS HNSW vs Lucene.",{"type":42,"tag":169,"props":229,"children":230},{},[231],{"type":42,"tag":182,"props":232,"children":234},{"href":233},"references\u002Fsearch-semantic-search-guide.md",[235],{"type":42,"tag":79,"props":236,"children":238},{"className":237},[],[239],{"type":48,"value":233},{"type":42,"tag":147,"props":241,"children":242},{},[243,253],{"type":42,"tag":169,"props":244,"children":245},{},[246,251],{"type":42,"tag":57,"props":247,"children":248},{},[249],{"type":48,"value":250},"log-analytics",{"type":48,"value":252}," — Log search, observability, PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards. Splunk\u002FDatadog\u002FELK alternatives.",{"type":42,"tag":169,"props":254,"children":255},{},[256],{"type":42,"tag":182,"props":257,"children":259},{"href":258},"references\u002Flog-analytics-guide.md",[260],{"type":42,"tag":79,"props":261,"children":263},{"className":262},[],[264],{"type":48,"value":258},{"type":42,"tag":147,"props":266,"children":267},{},[268,278],{"type":42,"tag":169,"props":269,"children":270},{},[271,276],{"type":42,"tag":57,"props":272,"children":273},{},[274],{"type":48,"value":275},"trace-analytics",{"type":48,"value":277}," — Distributed traces with OpenTelemetry. Span queries, service maps, Data Prepper.",{"type":42,"tag":169,"props":279,"children":280},{},[281],{"type":42,"tag":182,"props":282,"children":284},{"href":283},"references\u002Ftrace-analytics-trace-queries.md",[285],{"type":42,"tag":79,"props":286,"children":288},{"className":287},[],[289],{"type":48,"value":283},{"type":42,"tag":51,"props":291,"children":292},{},[293,295,300],{"type":48,"value":294},"If a prompt spans capabilities (e.g., ",{"type":42,"tag":131,"props":296,"children":297},{},[298],{"type":48,"value":299},"\"migrate from Solr AND set up RAG on the new domain\"",{"type":48,"value":301},"), pick the dominant capability for the response and close with a one-line handoff to the other capability's entry-point ref.",{"type":42,"tag":112,"props":303,"children":305},{"id":304},"universal-rules-apply-to-all-capabilities",[306],{"type":48,"value":307},"Universal rules (apply to ALL capabilities)",{"type":42,"tag":51,"props":309,"children":310},{},[311],{"type":48,"value":312},"These rules apply to every response, regardless of capability. Capability-specific rules (sizing math, shape detection, Migration Assistant for Amazon OpenSearch Service capability matrix, k-NN engine selection) live in the entry-point references, not here.",{"type":42,"tag":314,"props":315,"children":316},"ul",{},[317,360,394,404,421,431,515],{"type":42,"tag":318,"props":319,"children":320},"li",{},[321,326,328,334,336,342,344,350,352,358],{"type":42,"tag":57,"props":322,"children":323},{},[324],{"type":48,"value":325},"Report header (every multi-section response).",{"type":48,"value":327}," Begin every multi-section response with a single fenced metadata block: ",{"type":42,"tag":79,"props":329,"children":331},{"className":330},[],[332],{"type":48,"value":333},"> Generated: \u003CISO 8601 timestamp> | Skill: amazon-opensearch-service v\u003CN>",{"type":48,"value":335},". Get the time by calling the ",{"type":42,"tag":79,"props":337,"children":339},{"className":338},[],[340],{"type":48,"value":341},"current_time",{"type":48,"value":343}," tool (returns ISO 8601 in UTC). Read the skill version from this file's frontmatter ",{"type":42,"tag":79,"props":345,"children":347},{"className":346},[],[348],{"type":48,"value":349},"version:",{"type":48,"value":351}," field. For one-line answers (terse FOCUSED_OPERATIONAL replies, anti-pattern refusals) the header is optional; for any multi-section deliverable it is REQUIRED. Place it immediately after the report title and before the first ",{"type":42,"tag":79,"props":353,"children":355},{"className":354},[],[356],{"type":48,"value":357},"##",{"type":48,"value":359}," heading.",{"type":42,"tag":318,"props":361,"children":362},{},[363,368,370,376,377,383,385,392],{"type":42,"tag":57,"props":364,"children":365},{},[366],{"type":48,"value":367},"No dollar estimates",{"type":48,"value":369}," (HARD CONSTRAINT). Never produce ",{"type":42,"tag":79,"props":371,"children":373},{"className":372},[],[374],{"type":48,"value":375},"$X\u002Fmonth",{"type":48,"value":86},{"type":42,"tag":79,"props":378,"children":380},{"className":379},[],[381],{"type":48,"value":382},"~$1,500",{"type":48,"value":384},", or any dollar figure. Route every cost question to ",{"type":42,"tag":182,"props":386,"children":390},{"href":387,"rel":388},"https:\u002F\u002Fcalculator.aws",[389],"nofollow",[391],{"type":48,"value":387},{"type":48,"value":393}," and stop. If a sub-reference contains dollar figures, treat them as informational context only and do NOT pass them through to the user.",{"type":42,"tag":318,"props":395,"children":396},{},[397,402],{"type":42,"tag":57,"props":398,"children":399},{},[400],{"type":48,"value":401},"No credential leakage",{"type":48,"value":403}," (HARD CONSTRAINT). Never include master usernames, KMS key ARNs, VPC endpoint URLs, instance IPs, or account IDs in generated output.",{"type":42,"tag":318,"props":405,"children":406},{},[407,412,414,419],{"type":42,"tag":57,"props":408,"children":409},{},[410],{"type":48,"value":411},"Pick one",{"type":48,"value":413}," for every A-vs-B decision. Name a primary recommendation in one line with a one-sentence reason. A ",{"type":42,"tag":131,"props":415,"children":416},{},[417],{"type":48,"value":418},"\"go with B if...\"",{"type":48,"value":420}," caveat is allowed AFTER the primary; never lead with conditional-only guidance.",{"type":42,"tag":318,"props":422,"children":423},{},[424,429],{"type":42,"tag":57,"props":425,"children":426},{},[427],{"type":48,"value":428},"Source restatement.",{"type":48,"value":430}," The first 2–3 sentences must restate the source (engine + version + scale) when known, or restate the customer's question in concrete terms. The very first text the user sees must NOT be tool narration, meta-commentary, the report title, or simply restating the question verbatim.",{"type":42,"tag":318,"props":432,"children":433},{},[434,439,441,446,447,452,453,458,459,464,465,470,471,476,477,482,483,488,490,495,496,501,502,507,508,513],{"type":42,"tag":57,"props":435,"children":436},{},[437],{"type":48,"value":438},"No marketing tone.",{"type":48,"value":440}," Do NOT use ",{"type":42,"tag":131,"props":442,"children":443},{},[444],{"type":48,"value":445},"\"seamless\"",{"type":48,"value":86},{"type":42,"tag":131,"props":448,"children":449},{},[450],{"type":48,"value":451},"\"robust\"",{"type":48,"value":86},{"type":42,"tag":131,"props":454,"children":455},{},[456],{"type":48,"value":457},"\"best-in-class\"",{"type":48,"value":86},{"type":42,"tag":131,"props":460,"children":461},{},[462],{"type":48,"value":463},"\"production-hardened\"",{"type":48,"value":86},{"type":42,"tag":131,"props":466,"children":467},{},[468],{"type":48,"value":469},"\"enterprise-grade\"",{"type":48,"value":86},{"type":42,"tag":131,"props":472,"children":473},{},[474],{"type":48,"value":475},"\"world-class\"",{"type":48,"value":86},{"type":42,"tag":131,"props":478,"children":479},{},[480],{"type":48,"value":481},"\"cleanly\"",{"type":48,"value":86},{"type":42,"tag":131,"props":484,"children":485},{},[486],{"type":48,"value":487},"\"elegant\"",{"type":48,"value":489},". Do NOT stack 3+ vague hedges (",{"type":42,"tag":131,"props":491,"children":492},{},[493],{"type":48,"value":494},"\"typically\"",{"type":48,"value":86},{"type":42,"tag":131,"props":497,"children":498},{},[499],{"type":48,"value":500},"\"generally\"",{"type":48,"value":86},{"type":42,"tag":131,"props":503,"children":504},{},[505],{"type":48,"value":506},"\"usually\"",{"type":48,"value":86},{"type":42,"tag":131,"props":509,"children":510},{},[511],{"type":48,"value":512},"\"in most cases\"",{"type":48,"value":514},") in a single recommendation — be specific about when it does and does not apply.",{"type":42,"tag":318,"props":516,"children":517},{},[518,523,525,529,531],{"type":42,"tag":57,"props":519,"children":520},{},[521],{"type":48,"value":522},"Cross-capability handoff.",{"type":48,"value":524}," When a user prompt spans capabilities (e.g., ",{"type":42,"tag":131,"props":526,"children":527},{},[528],{"type":48,"value":299},{"type":48,"value":530},"), pick the dominant capability for the response, then close with a one-line handoff: ",{"type":42,"tag":131,"props":532,"children":533},{},[534,536,546],{"type":48,"value":535},"\"For \u003Cother capability>, see ",{"type":42,"tag":182,"props":537,"children":539},{"href":538},"...",[540],{"type":42,"tag":79,"props":541,"children":543},{"className":542},[],[544],{"type":48,"value":545},"references\u002F\u003Cother-capability>-\u003Centry>.md",{"type":48,"value":547},".\"",{"type":42,"tag":112,"props":549,"children":551},{"id":550},"cross-cutting-references-used-across-multiple-capabilities",[552],{"type":48,"value":553},"Cross-cutting references (used across multiple capabilities)",{"type":42,"tag":51,"props":555,"children":556},{},[557],{"type":48,"value":558},"These references are not capability-prefixed because they apply across capabilities. Capability entry-point references load them when relevant; SKILL.md never loads them directly.",{"type":42,"tag":314,"props":560,"children":561},{},[562,576,590,604,618,632,654],{"type":42,"tag":318,"props":563,"children":564},{},[565,574],{"type":42,"tag":182,"props":566,"children":568},{"href":567},"references\u002Fsizing.md",[569],{"type":42,"tag":79,"props":570,"children":572},{"className":571},[],[573],{"type":48,"value":567},{"type":48,"value":575}," — sizing math, instance family details, OR1 trade-offs, watermarks, JVM heap rules.",{"type":42,"tag":318,"props":577,"children":578},{},[579,588],{"type":42,"tag":182,"props":580,"children":582},{"href":581},"references\u002Fvector-knn.md",[583],{"type":42,"tag":79,"props":584,"children":586},{"className":585},[],[587],{"type":48,"value":581},{"type":48,"value":589}," — k-NN engines, memory math, RAG ingestion patterns, ELSER alternatives.",{"type":42,"tag":318,"props":591,"children":592},{},[593,602],{"type":42,"tag":182,"props":594,"children":596},{"href":595},"references\u002Fobservability.md",[597],{"type":42,"tag":79,"props":598,"children":600},{"className":599},[],[601],{"type":48,"value":595},{"type":48,"value":603}," — log analytics patterns, ISM, UltraWarm\u002FCold tiering, Splunk\u002FDatadog migration playbooks.",{"type":42,"tag":318,"props":605,"children":606},{},[607,616],{"type":42,"tag":182,"props":608,"children":610},{"href":609},"references\u002Fsecurity.md",[611],{"type":42,"tag":79,"props":612,"children":614},{"className":613},[],[615],{"type":48,"value":609},{"type":48,"value":617}," — FGAC, encryption, VPC patterns, audit logs, compliance posture.",{"type":42,"tag":318,"props":619,"children":620},{},[621,630],{"type":42,"tag":182,"props":622,"children":624},{"href":623},"references\u002Fpersonas.md",[625],{"type":42,"tag":79,"props":626,"children":628},{"className":627},[],[629],{"type":48,"value":623},{"type":48,"value":631}," — communication style per persona.",{"type":42,"tag":318,"props":633,"children":634},{},[635,644,646,652],{"type":42,"tag":182,"props":636,"children":638},{"href":637},"references\u002Fassessment-gotchas.md",[639],{"type":42,"tag":79,"props":640,"children":642},{"className":641},[],[643],{"type":48,"value":637},{"type":48,"value":645}," — production gotcha catalog (cite by number in Migration specifics or Risks\u002Fblockers tables; each gotcha carries a ",{"type":42,"tag":79,"props":647,"children":649},{"className":648},[],[650],{"type":48,"value":651},"Category:",{"type":48,"value":653}," tag that determines its lane).",{"type":42,"tag":318,"props":655,"children":656},{},[657,666],{"type":42,"tag":182,"props":658,"children":660},{"href":659},"references\u002Fassessment-knowledge-retrieval.md",[661],{"type":42,"tag":79,"props":662,"children":664},{"className":663},[],[665],{"type":48,"value":659},{"type":48,"value":667}," — topic → tool → URL recipe for batched verification.",{"type":42,"tag":51,"props":669,"children":670},{},[671,673,679],{"type":48,"value":672},"Assets (",{"type":42,"tag":79,"props":674,"children":676},{"className":675},[],[677],{"type":48,"value":678},"assets\u002F",{"type":48,"value":680},"): report templates for FULL_ASSESSMENT renderings (Solr-source, ES-source, executive summary).",{"type":42,"tag":112,"props":682,"children":684},{"id":683},"what-this-skill-does-not-do",[685],{"type":48,"value":686},"What this skill does NOT do",{"type":42,"tag":314,"props":688,"children":689},{},[690,707,717,727,737],{"type":42,"tag":318,"props":691,"children":692},{},[693,698,700,705],{"type":42,"tag":57,"props":694,"children":695},{},[696],{"type":48,"value":697},"Estimate dollar costs.",{"type":48,"value":699}," Pricing changes monthly and account-specific (RI, Savings Plan, EDP) discount math is outside this skill's reliable scope. Use ",{"type":42,"tag":182,"props":701,"children":703},{"href":387,"rel":702},[389],[704],{"type":48,"value":387},{"type":48,"value":706},".",{"type":42,"tag":318,"props":708,"children":709},{},[710,715],{"type":42,"tag":57,"props":711,"children":712},{},[713],{"type":48,"value":714},"Move data.",{"type":48,"value":716}," Use Migration Assistant for Amazon OpenSearch Service (Historical Data Migration for backfill, Live Traffic Migration for live cutover).",{"type":42,"tag":318,"props":718,"children":719},{},[720,725],{"type":42,"tag":57,"props":721,"children":722},{},[723],{"type":48,"value":724},"Build embedding models.",{"type":48,"value":726}," Use Amazon Bedrock or SageMaker.",{"type":42,"tag":318,"props":728,"children":729},{},[730,735],{"type":42,"tag":57,"props":731,"children":732},{},[733],{"type":48,"value":734},"Replace Splunk SPL or Datadog APM 1:1.",{"type":48,"value":736}," Some queries \u002F detectors \u002F dashboards need rewriting.",{"type":42,"tag":318,"props":738,"children":739},{},[740,745,747,753],{"type":42,"tag":57,"props":741,"children":742},{},[743],{"type":48,"value":744},"Tune relevance for a specific catalog.",{"type":48,"value":746}," Use OpenSearch Benchmark ",{"type":42,"tag":79,"props":748,"children":750},{"className":749},[],[751],{"type":48,"value":752},"big5",{"type":48,"value":754}," workload + your own judgment list.",{"items":756,"total":860},[757,774,789,804,819,829,844],{"slug":758,"name":758,"fn":759,"description":760,"org":761,"tags":762,"stars":24,"repoUrl":25,"updatedAt":773},"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},[763,766,769,770],{"name":764,"slug":765,"type":15},"Agents","agents",{"name":767,"slug":768,"type":15},"Automation","automation",{"name":23,"slug":8,"type":15},{"name":771,"slug":772,"type":15},"Engineering","engineering","2026-07-12T08:42:53.812877",{"slug":775,"name":775,"fn":776,"description":777,"org":778,"tags":779,"stars":24,"repoUrl":25,"updatedAt":788},"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},[780,781,784,787],{"name":764,"slug":765,"type":15},{"name":782,"slug":783,"type":15},"API Development","api-development",{"name":785,"slug":786,"type":15},"Authentication","authentication",{"name":23,"slug":8,"type":15},"2026-07-16T06:00:38.866147",{"slug":790,"name":790,"fn":791,"description":792,"org":793,"tags":794,"stars":24,"repoUrl":25,"updatedAt":803},"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},[795,796,797,800],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":798,"slug":799,"type":15},"Debugging","debugging",{"name":801,"slug":802,"type":15},"Observability","observability","2026-07-16T06:00:44.679093",{"slug":805,"name":805,"fn":806,"description":807,"org":808,"tags":809,"stars":24,"repoUrl":25,"updatedAt":818},"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},[810,811,812,815],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":813,"slug":814,"type":15},"CI\u002FCD","ci-cd",{"name":816,"slug":817,"type":15},"Deployment","deployment","2026-07-12T08:42:55.059577",{"slug":820,"name":820,"fn":821,"description":822,"org":823,"tags":824,"stars":24,"repoUrl":25,"updatedAt":828},"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},[825,826,827],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":816,"slug":817,"type":15},"2026-07-12T08:42:51.963247",{"slug":830,"name":830,"fn":831,"description":832,"org":833,"tags":834,"stars":24,"repoUrl":25,"updatedAt":843},"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},[835,836,837,840],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":838,"slug":839,"type":15},"Best Practices","best-practices",{"name":841,"slug":842,"type":15},"Security","security","2026-07-16T06:00:42.174705",{"slug":845,"name":845,"fn":846,"description":847,"org":848,"tags":849,"stars":24,"repoUrl":25,"updatedAt":859},"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},[850,851,852,855,856],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":853,"slug":854,"type":15},"Evals","evals",{"name":801,"slug":802,"type":15},{"name":857,"slug":858,"type":15},"Performance","performance","2026-07-12T08:42:56.488105",114,{"items":862,"total":979},[863,870,877,884,891,897,904,912,929,942,954,969],{"slug":758,"name":758,"fn":759,"description":760,"org":864,"tags":865,"stars":24,"repoUrl":25,"updatedAt":773},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[866,867,868,869],{"name":764,"slug":765,"type":15},{"name":767,"slug":768,"type":15},{"name":23,"slug":8,"type":15},{"name":771,"slug":772,"type":15},{"slug":775,"name":775,"fn":776,"description":777,"org":871,"tags":872,"stars":24,"repoUrl":25,"updatedAt":788},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[873,874,875,876],{"name":764,"slug":765,"type":15},{"name":782,"slug":783,"type":15},{"name":785,"slug":786,"type":15},{"name":23,"slug":8,"type":15},{"slug":790,"name":790,"fn":791,"description":792,"org":878,"tags":879,"stars":24,"repoUrl":25,"updatedAt":803},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[880,881,882,883],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":798,"slug":799,"type":15},{"name":801,"slug":802,"type":15},{"slug":805,"name":805,"fn":806,"description":807,"org":885,"tags":886,"stars":24,"repoUrl":25,"updatedAt":818},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[887,888,889,890],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":813,"slug":814,"type":15},{"name":816,"slug":817,"type":15},{"slug":820,"name":820,"fn":821,"description":822,"org":892,"tags":893,"stars":24,"repoUrl":25,"updatedAt":828},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[894,895,896],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":816,"slug":817,"type":15},{"slug":830,"name":830,"fn":831,"description":832,"org":898,"tags":899,"stars":24,"repoUrl":25,"updatedAt":843},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[900,901,902,903],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":838,"slug":839,"type":15},{"name":841,"slug":842,"type":15},{"slug":845,"name":845,"fn":846,"description":847,"org":905,"tags":906,"stars":24,"repoUrl":25,"updatedAt":859},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[907,908,909,910,911],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":853,"slug":854,"type":15},{"name":801,"slug":802,"type":15},{"name":857,"slug":858,"type":15},{"slug":913,"name":913,"fn":914,"description":915,"org":916,"tags":917,"stars":24,"repoUrl":25,"updatedAt":928},"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},[918,919,922,925],{"name":23,"slug":8,"type":15},{"name":920,"slug":921,"type":15},"Database","database",{"name":923,"slug":924,"type":15},"MySQL","mysql",{"name":926,"slug":927,"type":15},"Serverless","serverless","2026-07-12T08:43:13.27939",{"slug":930,"name":930,"fn":931,"description":932,"org":933,"tags":934,"stars":24,"repoUrl":25,"updatedAt":941},"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},[935,936,937,940],{"name":23,"slug":8,"type":15},{"name":920,"slug":921,"type":15},{"name":938,"slug":939,"type":15},"PostgreSQL","postgresql",{"name":926,"slug":927,"type":15},"2026-07-16T06:00:34.789624",{"slug":943,"name":943,"fn":944,"description":945,"org":946,"tags":947,"stars":24,"repoUrl":25,"updatedAt":953},"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},[948,949,950],{"name":764,"slug":765,"type":15},{"name":23,"slug":8,"type":15},{"name":951,"slug":952,"type":15},"LLM","llm","2026-07-25T05:30:35.20899",{"slug":955,"name":955,"fn":956,"description":957,"org":958,"tags":959,"stars":24,"repoUrl":25,"updatedAt":968},"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},[960,961,962,965],{"name":23,"slug":8,"type":15},{"name":920,"slug":921,"type":15},{"name":963,"slug":964,"type":15},"MongoDB","mongodb",{"name":966,"slug":967,"type":15},"NoSQL","nosql","2026-07-12T08:43:00.455878",{"slug":970,"name":970,"fn":971,"description":972,"org":973,"tags":974,"stars":24,"repoUrl":25,"updatedAt":978},"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},[975,976,977],{"name":23,"slug":8,"type":15},{"name":920,"slug":921,"type":15},{"name":966,"slug":967,"type":15},"2026-07-16T06:00:37.690386",115]