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amazon-opensearch-service

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.

72

Quality

91%

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An exemplary hub-and-spoke router: SKILL.md stays lean, delegates all capability detail to real, well-indexed entry-point references, and gives unusually concrete universal rules (exact header template, named CLI commands, hard constraints). The main trim opportunities are the duplicated cross-capability handoff rule and the absence of any validation checkpoint at the routing level itself.

Suggestions

State the cross-capability handoff rule once — it currently appears both at the end of Step 0 and again as a 'Cross-capability handoff' universal rule with near-identical wording; keep only the universal-rules instance.

Name the individual assets/ template files (e.g., solr-report-template.md, executive-summary-template.md) in the assets line so the FULL_ASSESSMENT rendering path is discoverable from SKILL.md without loading an entry-point reference first.

Add a one-line checkpoint after loading an entry-point reference (e.g., confirm the reference's 'When to use this capability' triggers match the prompt before proceeding) to close the workflow's only validation gap.

DimensionReasoningScore

Conciseness

The body is a lean router — every section carries load (Step 0 table, universal rules, cross-cutting ref index, non-goals, MCP-vs-local guardrail) with no explanations of concepts Claude already knows. It falls short of 5 mainly because the cross-capability handoff rule is stated twice ("If a prompt spans capabilities (e.g., \"migrate from Solr AND set up RAG...\")" in Step 0 and again verbatim as a universal rule) and the guardrail section runs long. Not a 3 — there is no padded or unnecessary explanation, just minor duplication to trim.

4 / 5

Actionability

Guidance is concrete and executable throughout: a copy-paste report-header template ("> Generated: <ISO 8601 timestamp> | Skill: amazon-opensearch-service v<N>") with the exact tool to call ("the `current_time` tool") and where to read the version; named commands ("aws opensearch describe-domain", "aws opensearchserverless create-collection", "awscurl" for SigV4); exact entry-point file links per capability; and exact handoff phrasing. For an instruction/routing skill this meets the fully-actionable top anchor, and per the rubric's code-vs-instruction note the absence of code blocks is not penalized.

5 / 5

Workflow Clarity

The sequence is crisp and unambiguous: "Step 0: detect the capability — first thing you do", state the detected capability in the first sentence with an example utterance, load the named entry-point reference, with an explicit fallback rule for multi-capability prompts and per-capability routing table. It is not 5 because the body itself contains no validation/checkpoint steps (e.g., verifying the loaded reference matches the detected capability) — checkpoints are delegated to the entry-point references, leaving a minor gap at this level; not 3 because the routing sequence is complete and explicit with a clear single entry action.

4 / 5

Progressive Disclosure

SKILL.md is a clear overview that holds no capability detail itself ("Everything else ... lives in the entry-point reference") and points to six well-signaled entry-point references, all of which exist in the bundle, plus an explicitly labeled cross-cutting reference list. Each entry-point reference verified in the bundle carries a complete capability index ("There are NO other provisioning files outside references/provisioning-*.md"), so the second hop is fully indexed and easy to navigate rather than buried. Not 4 — the only nit is that assets/ are described generically ("report templates for FULL_ASSESSMENT renderings") without naming individual files, which does not impair navigation.

5 / 5

Total

18

/

20

Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A dense, highly specific description that explicitly states both what the skill does and when to use it, with an unusually rich trigger list mixing product names, abbreviations, and natural user phrasing. The only weakness is a handful of unqualified broad triggers (RAG, analyze logs, root cause analysis) that create minor conflict risk with adjacent skills.

DimensionReasoningScore

Specificity

The description enumerates six capabilities each with concrete actions — "migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover)", "search (vector / semantic / hybrid / RAG with Bedrock)", "log-analytics (PPL, OSI, anomaly detection, Dashboards)" — matching the anchor for multiple specific concrete actions with comprehensive coverage. It is not the level below (4) because coverage spans every advertised capability with named operations rather than leaving minor gaps.

5 / 5

Completeness

It explicitly answers "what" ("Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless") and "when" (the explicit "Triggers on..." clause with concrete trigger phrases), matching the top anchor. A missing or weakly implied trigger clause would cap it at 3, but the trigger guidance is explicit.

5 / 5

Trigger Term Quality

"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" covers product names, abbreviations, technical synonyms, and natural user phrases — the comprehensive-synonyms anchor. It is not a 4 because both jargon and colloquial phrasings users would actually say are present.

5 / 5

Distinctiveness Conflict Risk

The niche is clear (Amazon OpenSearch Service/Serverless with product-specific triggers like AOSS, UltraWarm, OR1, Migration Assistant), but broad trigger terms such as "RAG", "analyze logs", and "root cause analysis" could also fire for generic RAG or observability skills — minor overlap risk with closely related skills, the anchor-4 case. It is not a 5 because those generic phrases are not qualified to the OpenSearch context; not a 3 because the core identity is unmistakably product-specific.

4 / 5

Total

19

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

14

/

16

Passed

Repository
aws/agent-toolkit-for-aws
Reviewed

Table of Contents

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