AD elasticsearch-openclaw
Read-only Elasticsearch 9.x reference for AI-orchestrated search and analytics. SECURITY: This skill provides documentation for read-only operations only (search, aggregations, analytics). No write/update/delete operations are included. Covers: (1) Semantic search with JINA embeddings via Elastic Inference API, (2) semantic_text field type with automatic embedding, (3) kNN vector search with dense_vector mappings, (4) Hybrid search combining BM25 + kNN with RRF, (5) Classic patterns: mappings, text/keyword fields, analyzers, boolean queries, aggregations, pagination, (6) Elasticsearch Python client 9.x — no body= parameter, keyword args, (7) Read-only API key creation with least-privilege scoping.
Read-only Elasticsearch 9.x reference for AI-orchestrated search and analytics. SECURITY: This skill provides documentation for read-only operations only…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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low Exfiltration
net-credential-useSKILL.md:54Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)curl -s "$ELASTICSEARCH_URL" -H "Authorization: ApiKey $ELASTICSEARCH_API_KEY"
security skill
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 46/100
- 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 801 tokens
- 100Running it twice. No mutating operations
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 706: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.