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web_data_facebook_marketplace_listings

Extract structured data from Facebook Marketplace listings using URLs to access product information without manual scraping.

Instructions

Quickly read structured Facebook marketplace listing data. Requires a valid Facebook marketplace listing URL. This can be a cache lookup, so it can be more reliable than scraping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Implementation Reference

  • Core handler logic for web_data_facebook_marketplace_listings: triggers BrightData dataset 'gd_lvt9iwuh6fbcwmx1a' collection via API POST, polls snapshot status up to 600 attempts, returns JSON data when ready.
    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 ${max_attempts} seconds waiting `
            +`for data`);
    }),
  • Schema definition: input 'url' (z.string().url()), description for the tool, and dataset_id used in handler.
        id: 'facebook_marketplace_listings',
        dataset_id: 'gd_lvt9iwuh6fbcwmx1a',
        description: [
            'Quickly read structured Facebook marketplace listing data.',
            'Requires a valid Facebook marketplace listing URL.',
            'This can be a cache lookup, so it can be more reliable than scraping',
        ].join('\n'),
        inputs: ['url'],
    },
  • server.js:674-745 (registration)
    Registration code: loops over datasets array (including facebook_marketplace_listings), dynamically creates tool spec with name 'web_data_<id>', zod schema from inputs, and handler, calls server.addTool().
    for (let {dataset_id, id, description, inputs, defaults = {}} of datasets)
    {
        let parameters = {};
        for (let input of inputs)
        {
            let param_schema = input=='url' ? z.string().url() : z.string();
            parameters[input] = defaults[input] !== undefined ?
                param_schema.default(defaults[input]) : param_schema;
        }
        addTool({
            name: `web_data_${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`);
            }),
        });
    }
  • Helper function tool_fn that wraps the raw handler: adds rate limiting, usage stats tracking, execution logging, error handling with API-specific messages, and timing logs.
    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);
            }
        };
    }
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. It discloses that this is a read operation ('read'), mentions reliability aspects ('cache lookup', 'more reliable than scraping'), and notes a prerequisite ('Requires a valid... URL'). However, it lacks details on error handling, rate limits, authentication needs, or what 'structured data' specifically includes.

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 with three short sentences that are front-loaded with the core purpose. Every sentence adds value: the first states what it does, the second specifies the input requirement, and the third explains a key behavioral trait. Zero wasted words.

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?

For a tool with no annotations, 1 parameter, no output schema, and low schema coverage, the description provides basic purpose and usage context but is incomplete. It doesn't explain what 'structured data' returns, error conditions, or how the cache lookup works. Given the complexity (reading web data) and lack of structured fields, more behavioral details would be helpful.

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

Parameters3/5

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 meaning by specifying that the 'url' parameter must be 'a valid Facebook marketplace listing URL,' which clarifies the expected content beyond just a URI format. This compensates somewhat for the low schema coverage, but doesn't provide examples or format details.

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 Facebook marketplace listing data.' It specifies the verb ('read'), resource ('Facebook marketplace listing data'), and quality ('structured'). However, it doesn't explicitly differentiate from sibling tools like 'scrape_as_html' or 'scrape_as_markdown' beyond mentioning it's 'more reliable than scraping'.

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 Facebook marketplace listing URL' and 'This can be a cache lookup, so it can be more reliable than scraping.' This implies when to use it (for Facebook marketplace listings, preferring reliability) but doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling scraping 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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