SKILLEMALL.ai
GitHub ↗ RU Sign in

AC test-environments

Design environment strategy for testing across dev, CI, preview, staging, and production — Docker Compose test infrastructure, multi-stage Dockerfiles, seed-data lifecycle, per-PR preview environments, production parity, and external-dependency stubbing at the HTTP boundary. Use when: "set up test environment," "docker-compose for tests," "per-PR preview environment," "staging parity," "spin up test infra," "environment tiers." Not for: choosing mock-vs-stub-vs-fake per dependency — use service-virtualization; factory and fixture data patterns — use test-data-management; pipeline/Actions config — use ci-cd-integration. Related: test-data-management, ci-cd-integration, contract-testing, service-virtualization.

petrkindlmann/qa-skills Agent Skills author: petrkindlmann MIT 3 files body ≈ 4 389 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Design environment strategy for testing across dev, CI, preview, staging, and production — Docker Compose test infrastructure, multi-stage Dockerfiles…

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

ProcedureDockerGitHubPostgreSQLStripeInfrastructuretype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
98
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

    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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 224): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 59/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
    • 70Execution cost. Instruction body is 4389 tokens
    • 100Steps. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • low 11 top-level sections: this looks like several domains in one skill

    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

    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 718: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 33 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 98.