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AB qa-handoff-package

Turn a story and its change into a clean 'ready for QA' package — test scenarios, edge cases, the data and environment setup, and what's explicitly out of scope. Use when asked to prep a QA handoff, what should QA test here, write test scenarios for this story, or make this ready for QA. Produces the scenarios mapped to acceptance criteria, the edge/negative cases devs forget, the exact data and environment setup to reproduce, the risk areas to probe, and the out-of-scope list so QA doesn't chase the wrong things.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 923 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Turn a story and its change into a clean 'ready for QA' package — test scenarios, edge cases, the data and environment setup, and what's explicitly out of…

As a process B 79/100 · Nearly there — weak spots: failures and branches, progress reporting

GeneratorData and analyticstype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
79/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
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: qa-handoff-package (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 · 0

    ✓ No critical or high findings

    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 79/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 923 tokens
    • 100Running it twice. No mutating operations

    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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 519: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 34 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.