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BC asc-testflight-orchestration

Orchestrate TestFlight distribution, groups, testers, and What to Test notes using asc. Use when rolling out betas.

The skillemall take

Promises to automate TestFlight beta rollouts: manage tester groups, distribute builds, and sync test notes via App Store Connect CLI. The skill contains one instruction file (545 tokens) with no scripts. Checks show: grade B, quality score 77, no critical issues, but process score only 51%. No sandbox run or model testing.

Works as a reference workflow for those already using asc-cli—saves time on repetitive commands. For others, it's just documentation. Install if you're rolling out betas regularly and want a standardized command sequence.

rorkai/app-store-connect-cli-skills Agent Skills author: rorkai 1 file body ≈ 545 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Orchestrate TestFlight distribution, groups, testers, and What to Test notes using asc.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

Proceduretype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 23 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 545 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 115: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 23 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.