ClawHub

Ai Voc Review Insights

v1.0.0

AI-powered Voice of Customer (VoC) review intelligence agent using DeepSeek-style analysis. Deep semantic analysis of customer reviews to extract pain points...

⭐ 0· 77·1 current·1 all-time
by@mguozhen
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
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Benign
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Benign
high confidence
✓
Purpose & Capability
Name, description, and runtime instructions all describe semantic VoC analysis of pasted reviews. There are no declared env vars, binaries, or installs that would be unrelated to text analysis, so the requested capabilities match the stated purpose.
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Instruction Scope
SKILL.md asks the user to paste 20–200 reviews and provides detailed analysis frameworks. It does not instruct the agent to read system files, access credentials, or call external endpoints. One minor oddity: the frontmatter lists allowed-tools: Bash, but the document contains no shell commands or install steps; this likely is harmless but could be clarified (it does not by itself cause network exfiltration).
✓
Install Mechanism
No install spec and no code files are present (instruction-only). Nothing will be written to disk or downloaded as part of installation.
✓
Credentials
The skill declares no required environment variables, credentials, or config paths. That is proportionate for a text-analysis instruction-only skill.
✓
Persistence & Privilege
always is false and the skill is user-invocable; it does not request elevated or persistent privileges beyond normal skill invocation.
Assessment
This is an instruction-only VoC analysis skill and appears internally consistent. Before using it: (1) avoid pasting sensitive personal data or credentials into the reviews you provide; (2) confirm how your agent/model provider logs or stores inputs (your reviews will be sent to the model for analysis); (3) if you want assurance about behavior, ask the publisher to explain the 'allowed-tools: Bash' frontmatter and to confirm the skill will not run shell commands or call external endpoints; (4) review the GitHub homepage/license if you need provenance. Overall the skill is coherent and low-risk, but treat any pasted customer data as potentially visible to the model/service.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

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