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AA multi-persona-user-story

Turn one feature concept into user stories and Gherkin-style acceptance criteria across 3-5 personas (new user, power user, admin, mobile, accessibility, read-only viewer). Writes stories in the canonical "As a / I want / So that" form against INVEST criteria, attaches Given-When-Then tests with happy-path and negative cases, and surfaces cross-persona conflicts. Trigger when the user says "write user stories", "draft acceptance criteria", "story map across personas", "split this feature by user type", or "Gherkin acceptance criteria for".

genspark Agent Skills author: Genspark 1 file body ≈ 1 917 tokens Open the sourcegenspark.ai↗ analyzed 3 d ago

As a process A 92/100 · Runs to the end — weak spots: running it twice, progress reporting

PersonaOperations and projectsResearchtype and topics are labelled automatically from the skill text
Runs in: Genspark 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
A
92/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
Inputs and preconditions w 11
70
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: 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 92/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 43 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1917 tokens

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 545: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 43 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.