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BF amazon-opensearch-service

Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk/Datadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector / k-NN / semantic / hybrid / 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/Datadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.

ClawHub Agent Skills author: Amazon Web Services 1 file body ≈ 1 788 tokens Open the sourceclawhub.ai↗ analyzed 25 h ago

Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation…

As a process F 44/100 · Will not run — References files that are not bundled: references/assessment-workflow.md, references/provisioning-reference.md, references/search-semantic-search-guide.md

AnalyzerAWSData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
53
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: references/assessment-workflow.md, references/provisioning-reference.md, references/search-semantic-search-guide.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/assessment-workflow.md
  • warning missing-ref reference to a missing file: references/provisioning-reference.md
  • warning missing-ref reference to a missing file: references/search-semantic-search-guide.md
  • warning missing-ref reference to a missing file: references/log-analytics-guide.md
  • warning missing-ref reference to a missing file: references/trace-analytics-trace-queries.md
  • warning missing-ref reference to a missing file: ...
  • warning missing-ref reference to a missing file: references/sizing.md
  • warning missing-ref reference to a missing file: references/vector-knn.md
  • warning missing-ref reference to a missing file: references/observability.md
  • warning missing-ref reference to a missing file: references/security.md
  • warning missing-ref reference to a missing file: references/personas.md
  • warning missing-ref reference to a missing file: references/assessment-gotchas.md
  • warning missing-ref reference to a missing file: references/assessment-knowledge-retrieval.md
  • warning missing-ref reference to a missing file: references/<other-capability>-<entry>.md

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: references/assessment-workflow.md, references/provisioning-reference.md, references/search-semantic-search-guide.md
  • 0Tools and files. 14 referenced file(s) missing: references/assessment-workflow.md, references/provisioning-reference.md, references/search-semantic-search-guide.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 30Running it twice. 1 mutating operations with no state check
  • 100Steps. 19 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1788 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (3 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 998: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 5 headings
  • +3Step-by-step instructions: 19 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.