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web_data_reuter_news

Extract structured Reuters news data from URLs for reliable analysis, using cache lookup to avoid scraping issues.

Instructions

Quickly read structured reuter news data. Requires a valid reuter news report URL. This can be a cache lookup, so it can be more reliable than scraping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Implementation Reference

  • The handler function for web_data_reuter_news (and other web_data tools). It triggers a BrightData dataset collection using the specific dataset_id 'gd_lyptx9h74wtlvpnfu' for Reuters news, polls for the snapshot to be ready (up to 600 attempts), and returns the JSON string of the result data.
    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 ${max_attempts} seconds waiting `
            +`for data`);
    }),
  • Dynamically generates the Zod schema for the tool's input parameters. For web_data_reuter_news, inputs=['url'], so parameters = {url: z.string().url()}.
    let parameters = {};
    for (let input of inputs)
    {
        let param_schema = input=='url' ? z.string().url() : z.string();
        parameters[input] = defaults[input] !== undefined ?
            param_schema.default(defaults[input]) : param_schema;
    }
  • server.js:579-587 (registration)
    Dataset configuration for 'reuter_news' which is used to register the tool 'web_data_reuter_news' with its specific dataset_id, description, and inputs.
        id: 'reuter_news',
        dataset_id: 'gd_lyptx9h74wtlvpnfu',
        description: [
            'Quickly read structured reuter news data.',
            'Requires a valid reuter news report URL.',
            'This can be a cache lookup, so it can be more reliable than scraping',
        ].join('\n'),
        inputs: ['url'],
    }, {
  • server.js:683-687 (registration)
    Registers the MCP tool by calling addTool with the constructed name `web_data_reuter_news` (when id='reuter_news'), description from dataset, Zod parameters schema, and wrapped execute handler.
    addTool({
        name: `web_data_${id}`,
        description,
        parameters: z.object(parameters),
        execute: tool_fn(`web_data_${id}`, async(data, ctx)=>{
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'), involves a cache lookup (implying potential performance benefits and data freshness considerations), and compares reliability to scraping. However, it lacks details on error handling, rate limits, authentication needs, or output format, which are important for a web data tool.

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

Conciseness4/5

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

The description is brief and front-loaded, with three concise sentences that each add value: stating the purpose, input requirement, and reliability benefit. There's no wasted text, though it could be slightly more structured (e.g., bullet points) for clarity.

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 moderate complexity (web data reading with caching), no annotations, no output schema, and low schema coverage, the description is somewhat incomplete. It covers the core purpose and input but lacks details on behavioral traits (e.g., caching behavior, error cases) and output format, which are important for effective use.

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, so the description must compensate. It specifies that the 'url' parameter must be 'a valid reuter news report URL,' adding crucial semantic context beyond the schema's generic URI format. This clearly defines the expected input, though it doesn't detail URL structure or validation rules.

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 reuter news data' specifies the verb ('read'), resource ('reuter news data'), and key characteristic ('structured'). It distinguishes from siblings by focusing on Reuters news specifically, though it doesn't explicitly contrast with other web_data_* tools for different sources.

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 reuter news report URL' and mentions it 'can be more reliable than scraping,' which implicitly suggests using this instead of scraping tools for Reuters content. However, it doesn't explicitly state when to use this versus other Reuters-specific tools (none listed) or general scraping alternatives, leaving some ambiguity.

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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