SKILLEMALL.ai
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AB signup-flow-cro

When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions "signup conversions," "registration friction," "signup form optimization," "free trial signup," "reduce signup dropoff," "account creation flow," "people aren't signing up," "signup abandonment," "trial conversion rate," "nobody completes registration," "too many steps to sign up," or "simplify our signup." Use this whenever the user has a signup or registration flow that isn't performing. For post-signup onboarding, see onboarding-cro. For lead capture forms (not account creation), see form-cro.

skytiger6724/qwen-skills Agent Skills author: skytiger6724 2 files body ≈ 2 415 tokens Open the sourcegithub.com↗ analyzed 2 d ago

When the user wants to optimize signup, registration, account creation, or trial activation flows.

As a process B 70/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
Runs in: Qwen Code Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS 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%
88
Run on models
none yet
Process rating
B
70/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 70/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 12 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Steps. 190 steps, 5 vague phrases
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2415 tokens
    • low 13 top-level sections: this looks like several domains in one skill
    • medium 6 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 12 example trigger phrases
    • +3Description length 632: enough signal without eating the budget
    • +4Structure: 46 headings
    • +3Step-by-step instructions: 190 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.