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AC alicloud-ai-audio-tts

Generate human-like speech audio with Model Studio DashScope Qwen TTS models (qwen3-tts-flash, qwen3-tts-instruct-flash). Use when converting text to speech, producing voice lines for short drama/news videos, or documenting TTS request/response fields for DashScope.

ClawHub Agent Skills author: cinience v1.0.4 MIT-0 6 files body ≈ 880 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 64/100 · Has gaps — weak spots: when it triggers, failures and branches

GeneratorInfrastructureMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
C
64/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Tools and files w 18
60
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: 6. 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 64/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 880 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 11 top-level sections: this looks like several domains in one skill

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 266: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 33 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: suspicious
    This is a mostly coherent Alibaba Cloud text-to-speech skill, but its helper script can send the API key to a request-supplied endpoint and then download an unvalidated returned URL.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026