SKILLEMALL.ai

AF integration-testing

Automated integration testing with external services using testcontainers, wiremock, localstack. Use when developer needs to set up integration tests for testing with real services in Docker containers via testcontainers, mocking HTTP APIs with WireMock, testing AWS S3 with LocalStack, SFTP integration testing, or setting up complex integration test environments with external dependencies.

ClawHub Agent Skills author: ahmed181283 v1.0.1 MIT-0 13 files body ≈ 1 056 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process F 30/100 · Will not run — References files that are not bundled: templates/localstack-s33-tests.py

IntegrationDockerAWSInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
F
30/100
Will not run
References files that are not bundled: templates/localstack-s33-tests.py
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. 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: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: templates/localstack-s33-tests.py

Process rating: all ten parameters 30/100

Will not run. References files that are not bundled: templates/localstack-s33-tests.py
  • 0Tools and files. 1 referenced file(s) missing: templates/localstack-s33-tests.py
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 85Steps. 28 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1056 tokens
  • 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 392: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

External checks

ClawHub: suspicious
This is a legitimate integration-testing skill, but some helper scripts make persistent host changes and install or execute external software without clear opt-in.
LLM: suspicious (high) · VirusTotal: · 29 May 2026