对文本执行 6 维度 60 分制综合质量评分。
AI agents call assess_quality to retrieve information from Aigc Humanizer Zh without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool reads and analyzes input text to produce a quality score across multiple dimensions. It is a read/analysis operation with no side effects — it does not modify, execute, or delete anything. The blast radius of misuse is low since it only returns a score.
From the tool's definition 对文本执行 6 维度 60 分制综合质量评分 (perform 6-dimension 60-point comprehensive quality scoring on text)
Attacks that exploit this kind of access
对文本执行 6 维度 60 分制综合质量评分。. It is categorised as a Read tool in the Aigc Humanizer Zh MCP Server, which means it retrieves data without modifying state.
Register the Aigc Humanizer Zh MCP server in PolicyLayer and add a rule for assess_quality: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Aigc Humanizer Zh. Nothing to install.
assess_quality is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the assess_quality rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for assess_quality. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
assess_quality is provided by the Aigc Humanizer Zh MCP server (shuohui-air-technology/aigc-humanizer-zh). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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