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xiaobenyang-com

Advertising-Analysis

ac

ac

Analyze advertising code to identify injection patterns in LLM responses, demonstrating risks of ad middleware in AI systems.

Instructions

ac

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Implementation Reference

  • Core handler function that forwards tool calls (including 'ac') to the remote API by making a POST request with toolName as 'func' header and arguments as body.
    const calcXiaoBenYangApi = async function (fullArgs: Record<string, any>) {
        // 发起 POST 请求
        let response = await fetch('https://mcp.xiaobenyang.com/api', {
            method: 'POST',
            headers: {
                'XBY-APIKEY': apiKey,
                'func': fullArgs.toolName,
                'mcpid': mcpID
            },
            body: new URLSearchParams(fullArgs)
        });
        const apiResult = await response.text();
    
        return {
            content: [
                {
                    type: "text",
                    text: apiResult // 将字符串结果放入 content 中
                }
            ]
        } as { [x: string]: unknown; content: [{ type: "text"; text: string }] };
    };
  • Wrapper handler registered for each tool, including 'ac', which adds the toolName to arguments and calls the core API forwarder.
    const handleXiaoBenYangApi = async (args: Record<string, any>, toolName: string) => {
        // 校验aid是否存在
        if (toolName === undefined || toolName === null) {
            throw new Error("缺少必要参数 'aid'");
        }
        // 合并参数
        const fullArgs = {...args, toolName: toolName};
        // 调用API
        return calcXiaoBenYangApi(fullArgs);
    };
  • src/mcp.ts:50-65 (registration)
    Helper function that registers a tool with the MCP server, called dynamically for each tool including 'ac', specifying the schema and the wrapper handler.
    const addToolXiaoBenYangApi = function (
        name: string,
        desc: string,
        params: Record<string, ZodType>
    ) {
        server.registerTool(
            name,
            {
                title: name,
                description: desc,
                inputSchema: params,
            }
            ,
            async (args: Record<string, any>) => handleXiaoBenYangApi(args, name)
        )
    };
  • src/mcp.ts:89-132 (registration)
    Dynamic registration loop that fetches tool list from remote, builds Zod schema for each (including 'ac'), and registers them using addToolXiaoBenYangApi.
    for (const apiDesc of apiDescList) {
        let inputSchema = JSON.parse(apiDesc.inputSchema);
        const zodDict: Record<string, z.ZodTypeAny> = {};
    
        Object.entries(inputSchema.properties).forEach(([name, propConfig]) => {
            let zodType;
            let pt = (propConfig as { type: string }).type;
            switch (pt) {
                case 'string':
                    zodType = z.string();
                    break;
                case 'number':
                    zodType = z.number();
                    break;
                case 'boolean':
                    zodType = z.boolean();
                    break;
                case 'integer':
                    zodType = z.int32();
                    break;
                case 'array':
                    zodType = z.array(z.any());
                    break;
                case 'object':
                    zodType = z.object(z.any());
                    break;
                default:
                    zodType = z.any();
            }
    
            if (inputSchema.required?.includes(name)) {
                zodDict[name] = zodType;
            } else {
                zodDict[name] = zodType.optional();
            }
        });
    
    
        addToolXiaoBenYangApi(
            apiDesc.name,
            apiDesc.description ? apiDesc.description : apiDesc.name,
            zodDict);
    }
  • Dynamic schema construction from remote tool descriptions, converting JSON schema types to Zod types for input validation of tools like 'ac'.
    Object.entries(inputSchema.properties).forEach(([name, propConfig]) => {
        let zodType;
        let pt = (propConfig as { type: string }).type;
        switch (pt) {
            case 'string':
                zodType = z.string();
                break;
            case 'number':
                zodType = z.number();
                break;
            case 'boolean':
                zodType = z.boolean();
                break;
            case 'integer':
                zodType = z.int32();
                break;
            case 'array':
                zodType = z.array(z.any());
                break;
            case 'object':
                zodType = z.object(z.any());
                break;
            default:
                zodType = z.any();
        }
    
        if (inputSchema.required?.includes(name)) {
            zodDict[name] = zodType;
        } else {
            zodDict[name] = zodType.optional();
        }
    });
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description 'ac' reveals nothing about the tool's behavior, such as whether it performs read/write operations, requires authentication, has side effects, or handles errors. It fails to compensate for the lack of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

While the description is extremely brief, this brevity results from under-specification rather than effective conciseness. The single word 'ac' fails to convey necessary information, making it inefficient and poorly structured for tool selection.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one parameter with 0% schema coverage, no annotations, no output schema, and multiple sibling tools, the description is completely inadequate. It provides no context to understand the tool's function, usage, or behavior, making it insufficient for effective agent operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, and the description 'ac' adds no information about the single required parameter 'code'. It does not explain what 'code' represents, its format, or its purpose, leaving the parameter completely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tautological: description restates name/title.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent with no information to make an informed decision among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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