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AB test-strategy-doc

Write a test strategy document from a feature spec, PRD, or system description. Use when asked to create a test plan, write a test strategy, define QA approach, or plan testing for a feature or release. Produces a complete test strategy with scope, risk assessment, test types, coverage targets, and a prioritised test case outline.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 1 507 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Write a test strategy document from a feature spec, PRD, or system description.

As a process B 71/100 · Nearly there — weak spots: failures and branches, running it twice

GeneratorPlaywrightSoftware developmentInfrastructureSecuritytype 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
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
83
Run on models
none yet
Process rating
B
71/100
Nearly there
Failures and branches w 10
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: test-strategy-doc (mohitagw15856/pm-claude-skills)

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Risky intent intent-offensive-security SKILL.md:79
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **Tools:** [e.g. OWASP ZAP, manual penetration testing, Snyk]

    Files scanned: 1. 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 71/100

    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 4 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 59 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1507 tokens
    • 100Progress reporting. Reports progress

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 332: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 59 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.