Neon Postgres
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Guides and best practices for working with Lakebase Postgres, the database behind Neon.
Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration…
Install Amazon Opensearch Service
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws/agent-toolkit-for-aws amazon-opensearch-service --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/aws-data-analytics/skills/amazon-opensearch-service .claude/skills/amazon-opensearch-service && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "amazon-opensearch-service" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-service into .claude/skills/amazon-opensearch-service/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "amazon-opensearch-service", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-serviceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws/agent-toolkit-for-aws amazon-opensearch-service --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/aws-data-analytics/skills/amazon-opensearch-service .agents/skills/amazon-opensearch-service && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "amazon-opensearch-service" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-service into .agents/skills/amazon-opensearch-service/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "amazon-opensearch-service", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws/agent-toolkit-for-aws amazon-opensearch-service --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/aws-data-analytics/skills/amazon-opensearch-service .cursor/skills/amazon-opensearch-service && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "amazon-opensearch-service" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-service into .cursor/skills/amazon-opensearch-service/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "amazon-opensearch-service", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aws/agent-toolkit-for-aws.git --path plugins/aws-data-analytics/skills/amazon-opensearch-service--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aws/agent-toolkit-for-aws amazon-opensearch-service --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/aws-data-analytics/skills/amazon-opensearch-service .gemini/skills/amazon-opensearch-service && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "amazon-opensearch-service" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-service into .gemini/skills/amazon-opensearch-service/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "amazon-opensearch-service", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aws/agent-toolkit-for-aws amazon-opensearch-serviceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/aws-data-analytics/skills/amazon-opensearch-service .github/skills/amazon-opensearch-service && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "amazon-opensearch-service" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-service into .github/skills/amazon-opensearch-service/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "amazon-opensearch-service", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aws/agent-toolkit-for-aws amazon-opensearch-service --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/aws-data-analytics/skills/amazon-opensearch-service .opencode/skills/amazon-opensearch-service && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "amazon-opensearch-service" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/amazon-opensearch-service into .opencode/skills/amazon-opensearch-service/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "amazon-opensearch-service", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
amazon-opensearch-service- GitHub stars
- 2.8k
- Token cost
- ~2.4k tokens
- SKILL.md length
- 997 words
- Files
- 59 (incl. references, assets)
- Skills in repo
- 138
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration…
- Vector/k-NN/semantic/hybrid search
- SKILL.md covers Step 0: detect the capability…, Universal rules (apply to ALL…, Cross-cutting references (used… and What this skill does NOT do, plus 1 more section
- Calls aws
- Trace analytics
What it does
Amazon Opensearch Service is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock); log-analytics (PPL, OSI, anomaly detection, Dashboards); trace-analytics (OTel spans, service maps, Data Prepper)…
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 60 other files, including reference files and assets (for example `assets/elasticsearch-gap-register.md`, `assets/elasticsearch-index-template-skeleton.md` and `assets/elasticsearch-report-template.md`).
It sits in Data & Analytics, covering Vector databases, Retrieval-augmented generation and Data analysis. It works with OpenSearch, Amazon Web Services, Elasticsearch and OpenTelemetry. The repository describes itself as: Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. The licence is Apache-2.0.
When your agent uses it
- Vector/k-NN/semantic/hybrid search
- Trace analytics
- Migration Assistant
- Investigate errors
Example prompts
- “Use the amazon-opensearch-service skill to guide migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows…”
- “/amazon-opensearch-service”
What it can do on your machine
Read from SKILL.md and the folder at commit 188af2f. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
aws
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
calculator.aws
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Amazon Opensearch Service loads about 2.4k tokens when it runs, and up to ~121k if it reads all its reference files. Until then it costs about 222 tokens; SKILL.md has 997 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from aws/agent-toolkit-for-aws at commit 188af2f, republished under its Apache-2.0 licence (© aws). 997 words, ~2,352 tokens.
Download SKILL.mdSave it as
.claude/skills/amazon-opensearch-service/SKILL.md (or your agent's skills folder). This skill also uses 58 other files; get the full folder from GitHub.- name
- amazon-opensearch-service
- description
- Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock); log-analytics (PPL, OSI, anomaly detection, Dashboards); trace-analytics (OTel spans, service maps, Data Prepper); ai-assistant (natural language data exploration, incident investigation, root cause analysis). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, Solr, vector/k-NN/semantic/hybrid search, RAG, log analytics, PPL, trace analytics, ISM, FAISS, HNSW, Migration Assistant, UltraWarm, OR1, query my data, analyze logs, investigate errors, root cause analysis.
- metadata.version
- 2
Amazon OpenSearch Service — the unified skill
This skill answers anything about Amazon OpenSearch Service or Serverless across six 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.
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, itscall_awstool offers a streamlined alternative — but every operation in this skill MUST work via the AWS CLI alone. Data-plane HTTP calls against AOS / AOSS useawscurlfor SigV4-signed requests; this works in both contexts.
Step 0: detect the capability — first thing you do
Pick one of the six 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.
| Capability | Entry-point reference |
|---|---|
| migration — Solr / Elasticsearch / self-managed OpenSearch into AOS or AOSS. Schema/query translation, sizing, cutover. | references/assessment-workflow.md |
| provisioning — Provisioning and managing AOS domains and AOSS collections. Lifecycle, upgrades, storage tiers, FGAC, monitoring. | references/provisioning-reference.md |
| search — Vector / semantic / hybrid / sparse / dense / RAG retrieval. Bedrock connectors, FAISS HNSW vs Lucene. | references/search-semantic-search-guide.md |
| log-analytics — Log search, observability, PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards. Splunk/Datadog/ELK alternatives. | references/log-analytics-guide.md |
| trace-analytics — Distributed traces with OpenTelemetry. Span queries, service maps, Data Prepper. | references/trace-analytics-trace-queries.md |
| ai-assistant — Agentic AI Assistant: auto-discovers indices, generates optimized PPL/DSL queries, summarizes results, and investigates incidents end-to-end. No manual query crafting needed. | references/ai-assistant.md |
If 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.
Universal rules (apply to ALL capabilities)
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.
- Report header (every multi-section response). Begin every multi-section response with a single fenced metadata block:
> Generated: <ISO 8601 timestamp> | Skill: amazon-opensearch-service v<N>. Get the time by calling thecurrent_timetool (returns ISO 8601 in UTC). Read the skill version from this file's frontmatterversion: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. - No dollar estimates (HARD CONSTRAINT). Never produce
$X/month,~$1,500, or any dollar figure. Route every cost question to https://calculator.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. - No credential leakage (HARD CONSTRAINT). Never include master usernames, KMS key ARNs, VPC endpoint URLs, instance IPs, or account IDs in generated output.
- 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.
- 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.
- 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.
- 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 <other capability>, see
references/<other-capability>-<entry>.md."
Show full SKILL.md (349 more words)Show less
Cross-cutting references (used across multiple capabilities)
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.
references/sizing.md— sizing math, instance family details, OR1 trade-offs, watermarks, JVM heap rules.references/vector-knn.md— k-NN engines, memory math, RAG ingestion patterns, ELSER alternatives.references/observability.md— log analytics patterns, ISM, UltraWarm/Cold tiering, Splunk/Datadog migration playbooks.references/security.md— FGAC, encryption, VPC patterns, audit logs, compliance posture.references/personas.md— communication style per persona.references/assessment-gotchas.md— production gotcha catalog (cite by number in Migration specifics or Risks/blockers tables; each gotcha carries aCategory:tag that determines its lane).references/assessment-knowledge-retrieval.md— topic → tool → URL recipe for batched verification.
Assets (assets/): report templates for FULL_ASSESSMENT renderings (Solr-source, ES-source, executive summary).
What this skill does NOT do
- Estimate dollar costs. Pricing changes monthly and account-specific (RI, Savings Plan, EDP) discount math is outside this skill's reliable scope. Use https://calculator.aws.
- Move data. Use Migration Assistant for Amazon OpenSearch Service (Historical Data Migration for backfill, Live Traffic Migration for live cutover).
- Build embedding models. Use Amazon Bedrock or SageMaker.
- Replace Splunk SPL or Datadog APM 1:1. Some queries / detectors / dashboards need rewriting.
- Tune relevance for a specific catalog. Use OpenSearch Benchmark
big5workload + your own judgment list.
Guardrail — where this skill's own files live (MCP vs local install)
This skill can be loaded two ways, and they resolve the skill's own bundled files from different places. Determine how the skill was loaded before reading a reference or running a script:
- Loaded through the AWS MCP server's
retrieve_skilltool: The skill is not installed on the local filesystem. You MUST fetch each reference or script viaretrieve_skillwith thefileparameter (e.g.file="references/architecture.md"orfile="scripts/deploy.py"), and run the script from the returned content. Do NOTfile_readthese paths locally — they do not exist on disk. - Installed locally (e.g.
.kiro/skills/your-skill/or~/.claude/skills/your-skill/): Read and run files from the local skill directory using relative paths.
This distinction applies only to the skill's own packaged files. User data and
session artifacts are always read from and written to the user's working
directory. Never fetch or write customer data through retrieve_skill.
© aws, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 58 other files (references, assets) in plugins/aws-data-analytics/skills/amazon-opensearch-service of aws/agent-toolkit-for-aws.
- SKILL.md
- assets/elasticsearch-gap-register.md
- assets/elasticsearch-index-template-skeleton.md
- assets/elasticsearch-report-template.md
- assets/executive-summary-template.md
- assets/report-template.md
- assets/solr-gap-register.md
- assets/solr-index-template-skeleton.md
- assets/solr-report-template.md
- assets/tech-deepdive-template.md
- references/ai-assistant.md
- references/assessment-gotchas.md
- references/assessment-knowledge-retrieval.md
- references/assessment-shape-anti-pattern-pushback.md
- references/assessment-shape-comparative-decision.md
- references/assessment-shape-focused-operational.md
- references/assessment-shape-full-assessment.md
- references/assessment-shape-overview.md
- references/assessment-shape-schema-conversion.md
- … and 40 more
Open the folder on GitHubat commit 188af2f
Compare with similar skills
Amazon Opensearch Service next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Amazon Opensearch Service this skillaws/agent-toolkit-for-aws | 2.8k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Neon Postgresusenotra/notra | 256 | — | ~4.1k | Automated safety check: Notes | AGPL-3.0 | |
| Neon Postgresneondatabase/agent-skills | 100 | — | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Create Retrieval PluginNomaDamas/AutoRAG-Research | 149 | — | ~728 | Automated safety check: Notes | Apache-2.0 | |
| Cloud Provisioningelastic/agent-skills | 592 | — | ~5.4k | Automated safety check: Pass | Apache-2.0 | |
| Opensearch Personalize Caching Strategiespproenca/dot-skills | 215 | — | ~4.8k | Automated safety check: Pass | MIT |
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Related
Questions about Amazon Opensearch Service
What does Amazon Opensearch Service do?
Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration…. Amazon Opensearch Service is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization.
When should I use Amazon Opensearch Service?
Amazon Opensearch Service fits situations like: vector/k-NN/semantic/hybrid search; trace analytics; migration Assistant; investigate errors.
How do I install Amazon Opensearch Service in Claude Code?
Run `npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a claude-code`. Or copy the skill folder (plugins/aws-data-analytics/skills/amazon-opensearch-service in aws/agent-toolkit-for-aws) into .claude/skills/amazon-opensearch-service in your project. Claude Code loads it when a task matches its description.
How do I install Amazon Opensearch Service in Codex?
Run `npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a codex`. Or copy the skill folder (plugins/aws-data-analytics/skills/amazon-opensearch-service in aws/agent-toolkit-for-aws) into .agents/skills/amazon-opensearch-service in your project. Codex loads it when a task matches its description.
Can I use Amazon Opensearch Service in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws/agent-toolkit-for-aws --skill amazon-opensearch-service -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/amazon-opensearch-service, .gemini/skills/amazon-opensearch-service, .github/skills/amazon-opensearch-service and .opencode/skills/amazon-opensearch-service in your project.
What does Amazon Opensearch Service need to run?
Going by SKILL.md and its folder, Amazon Opensearch Service needs the command-line tools its instructions call (aws).
Does Amazon Opensearch Service access the network?
SKILL.md names 1 domain. As links in the text: calculator.aws. This is read from the text; nothing was executed.
Is Amazon Opensearch Service safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Amazon Opensearch Service use?
Amazon Opensearch Service is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Amazon Opensearch Service use?
About 2.4k tokens (SKILL.md is roughly 9.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 119k tokens, read only when the agent opens those files.
What are the alternatives to Amazon Opensearch Service?
Skills that share tags, products or a category with Amazon Opensearch Service: Neon Postgres (usenotra/notra, 256 stars), Neon Postgres (neondatabase/agent-skills, 100 stars), Create Retrieval Plugin (NomaDamas/AutoRAG-Research, 149 stars) and Cloud Provisioning (elastic/agent-skills, 592 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Amazon Opensearch Service?
aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,825 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on October 7, 2026.
Source: aws/agent-toolkit-for-aws on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.