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web_data_amazon_product_reviews

Extract structured Amazon product review data using product URLs to analyze customer feedback and ratings without web scraping.

Instructions

Quickly read structured amazon product review data. Requires a valid product URL with /dp/ in it. This can be a cache lookup, so it can be more reliable than scraping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Implementation Reference

  • Handler function that triggers the BrightData dataset collection for the specified dataset_id ('gd_le8e811kzy4ggddlq' for amazon_product_reviews) and polls for the snapshot result up to 600 seconds.
    execute: tool_fn(`web_data_${id}`, async(data, ctx)=>{
        let trigger_response = await axios({
            url: 'https://api.brightdata.com/datasets/v3/trigger',
            params: {dataset_id, include_errors: true},
            method: 'POST',
            data: [data],
            headers: api_headers(),
        });
        if (!trigger_response.data?.snapshot_id)
            throw new Error('No snapshot ID returned from request');
        let snapshot_id = trigger_response.data.snapshot_id;
        console.error(`[web_data_${id}] triggered collection with `
            +`snapshot ID: ${snapshot_id}`);
        let max_attempts = 600;
        let attempts = 0;
        while (attempts < max_attempts)
        {
            try {
                if (ctx && ctx.reportProgress)
                {
                    await ctx.reportProgress({
                        progress: attempts,
                        total: max_attempts,
                        message: `Polling for data (attempt `
                            +`${attempts + 1}/${max_attempts})`,
                    });
                }
                let snapshot_response = await axios({
                    url: `https://api.brightdata.com/datasets/v3`
                        +`/snapshot/${snapshot_id}`,
                    params: {format: 'json'},
                    method: 'GET',
                    headers: api_headers(),
                });
                if (['running', 'building'].includes(snapshot_response.data?.status))
                {
                    console.error(`[web_data_${id}] snapshot not ready, `
                        +`polling again (attempt `
                        +`${attempts + 1}/${max_attempts})`);
                    attempts++;
                    await new Promise(resolve=>setTimeout(resolve, 1000));
                    continue;
                }
                console.error(`[web_data_${id}] snapshot data received `
                    +`after ${attempts + 1} attempts`);
                let result_data = JSON.stringify(snapshot_response.data);
                return result_data;
            } catch(e){
                console.error(`[web_data_${id}] polling error: `
                    +`${e.message}`);
                attempts++;
                await new Promise(resolve=>setTimeout(resolve, 1000));
            }
        }
        throw new Error(`Timeout after ${max_attempts} seconds waiting `
            +`for data`);
    }),
  • Generates the Zod input schema based on the 'inputs' array (['url'] for this tool), using z.string().url() for 'url' input.
    let parameters = {};
    for (let input of inputs)
    {
        let param_schema = input=='url' ? z.string().url() : z.string();
        parameters[input] = defaults[input] !== undefined ?
            param_schema.default(defaults[input]) : param_schema;
    }
  • server.js:287-295 (registration)
    Dataset configuration defining the tool's internal id, dataset_id, description, and inputs, used in the loop to register the tool as 'web_data_amazon_product_reviews' via addTool().
        id: 'amazon_product_reviews',
        dataset_id: 'gd_le8e811kzy4ggddlq',
        description: [
            'Quickly read structured amazon product review data.',
            'Requires a valid product URL with /dp/ in it.',
            'This can be a cache lookup, so it can be more reliable than scraping',
        ].join('\n'),
        inputs: ['url'],
    }, {
  • tool_fn wrapper applied to the handler: handles rate limiting, stats tracking, logging inputs/outputs/errors, and execution timing.
    function tool_fn(name, fn){
        return async(data, ctx)=>{
            check_rate_limit();
            debug_stats.tool_calls[name] = debug_stats.tool_calls[name]||0;
            debug_stats.tool_calls[name]++;
            debug_stats.session_calls++;
            let ts = Date.now();
            console.error(`[%s] executing %s`, name, JSON.stringify(data));
            try { return await fn(data, ctx); }
            catch(e){
                if (e.response)
                {
                    console.error(`[%s] error %s %s: %s`, name, e.response.status,
                        e.response.statusText, e.response.data);
                    let message = e.response.data;
                    if (message?.length)
                        throw new Error(`HTTP ${e.response.status}: ${message}`);
                }
                else
                    console.error(`[%s] error %s`, name, e.stack);
                throw e;
            } finally {
                let dur = Date.now()-ts;
                console.error(`[%s] tool finished in %sms`, name, dur);
            }
        };
    }
  • server.js:683-744 (registration)
    The addTool call within the loop that registers the tool with name `web_data_amazon_product_reviews`, its schema, description, and wrapped execute handler.
    addTool({
        name: `web_data_${id}`,
        description,
        parameters: z.object(parameters),
        execute: tool_fn(`web_data_${id}`, async(data, ctx)=>{
            let trigger_response = await axios({
                url: 'https://api.brightdata.com/datasets/v3/trigger',
                params: {dataset_id, include_errors: true},
                method: 'POST',
                data: [data],
                headers: api_headers(),
            });
            if (!trigger_response.data?.snapshot_id)
                throw new Error('No snapshot ID returned from request');
            let snapshot_id = trigger_response.data.snapshot_id;
            console.error(`[web_data_${id}] triggered collection with `
                +`snapshot ID: ${snapshot_id}`);
            let max_attempts = 600;
            let attempts = 0;
            while (attempts < max_attempts)
            {
                try {
                    if (ctx && ctx.reportProgress)
                    {
                        await ctx.reportProgress({
                            progress: attempts,
                            total: max_attempts,
                            message: `Polling for data (attempt `
                                +`${attempts + 1}/${max_attempts})`,
                        });
                    }
                    let snapshot_response = await axios({
                        url: `https://api.brightdata.com/datasets/v3`
                            +`/snapshot/${snapshot_id}`,
                        params: {format: 'json'},
                        method: 'GET',
                        headers: api_headers(),
                    });
                    if (['running', 'building'].includes(snapshot_response.data?.status))
                    {
                        console.error(`[web_data_${id}] snapshot not ready, `
                            +`polling again (attempt `
                            +`${attempts + 1}/${max_attempts})`);
                        attempts++;
                        await new Promise(resolve=>setTimeout(resolve, 1000));
                        continue;
                    }
                    console.error(`[web_data_${id}] snapshot data received `
                        +`after ${attempts + 1} attempts`);
                    let result_data = JSON.stringify(snapshot_response.data);
                    return result_data;
                } catch(e){
                    console.error(`[web_data_${id}] polling error: `
                        +`${e.message}`);
                    attempts++;
                    await new Promise(resolve=>setTimeout(resolve, 1000));
                }
            }
            throw new Error(`Timeout after ${max_attempts} seconds waiting `
                +`for data`);
        }),
    });
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context: the cache lookup behavior and reliability advantage over scraping. However, it doesn't cover other important aspects like rate limits, authentication needs, error conditions, or what 'structured data' specifically means in the output. For a tool with no annotations, this leaves significant gaps in behavioral understanding.

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

Conciseness5/5

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

The description is extremely concise and front-loaded: three sentences with zero waste. The first sentence states the core purpose, the second specifies the key parameter requirement, and the third adds important behavioral context. Every sentence earns its place without redundancy.

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

Completeness3/5

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

Given the tool's complexity (reading structured data from Amazon), no annotations, no output schema, and 0% schema description coverage, the description is minimally adequate. It covers the basic purpose, parameter requirement, and cache advantage, but lacks details on output format, error handling, limitations, and how it differs from sibling tools. This leaves the agent with significant gaps in understanding how to use it effectively.

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

Parameters4/5

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

The schema has 1 parameter with 0% description coverage. The description adds meaningful semantics: it specifies the parameter must be 'a valid product URL with /dp/ in it,' which provides crucial format requirements not in the schema. This compensates well for the low schema coverage, though it doesn't detail other constraints like URL validation rules or examples.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Quickly read structured amazon product review data.' It specifies the verb ('read'), resource ('amazon product review data'), and key characteristic ('structured'). However, it doesn't explicitly differentiate from sibling tools like 'web_data_amazon_product' or 'scrape_as_html', which would be needed for a score of 5.

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

Usage Guidelines3/5

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

The description provides some usage context: 'Requires a valid product URL with /dp/ in it' and 'This can be a cache lookup, so it can be more reliable than scraping.' This implies when to use it (for Amazon product reviews with specific URLs) and hints at advantages over scraping alternatives. However, it doesn't explicitly name when NOT to use it or directly compare to specific sibling tools like 'scrape_as_html' or 'web_data_amazon_product', keeping it at an implied rather than explicit level.

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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