SKILLEMALL.ai
GitHub ↗ RU Sign in

BB asc-app-create-ui

Create a new App Store Connect app record via browser automation. Use when there is no public API for app creation and you need an agent to drive the New App form.

The skillemall take

The skill automates App Store Connect app record creation via browser when the API is off-limits. Files hold one instruction at 1483 tokens with no critical errors or broken references. Scores: quality 84, process 70, safety 100. No model runs, no sandbox tests.

Your agent gets commands to fill the New App form. Without live model testing, it's unclear how it handles App Store Connect's dynamic UI or captchas if they show up. Worth installing if you're ready to debug on the fly—the skill is clean, just unproven.

rorkai/app-store-connect-cli-skills Agent Skills author: rorkai 1 file body ≈ 1 483 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Create a new App Store Connect app record via browser automation.

As a process B 70/100 · Nearly there — weak spots: result and completion, progress reporting

GeneratorAI and agentstype 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
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
70/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
50
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 70/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 47 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1483 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 163: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 47 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.