Webz.io News segmentation

Aggregate Webz News

aggregate_webz_news

Read-onlyIdempotent

Count news mentions instead of returning posts (GET /seg_api/news).

Aggregates people and companies mentioned in news around a topic. Example: people and companies mentioned around trump in the past week.

This is news only. Person and company counts are not meaningful on blogs or forums. It returns buckets with counts, not articles. Each underlying field request costs 1 credit. A response has at most 10 buckets. Returned from_offset values paginate through up to 100 buckets.

q is the same boolean language as search. A space means AND. days is the crawl lookback. Named site lists are q clauses, for example custom_sites_list:hot_sites. Default 7 is the past week. The maximum is 31. Older windows are reset to 3 days by the API; the supported maximum is 31 days.

field is the bucket. persons is people. organizations is companies. Default is both, as two requests. Any other segmentation field is allowed: thread.site, thread.site_suffix, thread.site_full, thread.site_section, thread.site_type, thread.country, thread.url, author, language, site_category, published, locations, persons, person.positive, person.negative, person.neutral, organizations, organization.positive, organization.negative, organization.neutral, trading_symbol.ticker, trading_symbol.exchange, thread.licensing_agency, sentiment, category, topic, rating, trust.bias, trust.category, trust.source.type. topic, sentiment, and the entity fields count meaningfully on news only.

Separate segmentation arguments: include_syndicated=true includes syndicated copies (default false). webz_reporter=true includes Webz Reporter posts (default false); this is a separate argument, not a q filter. from_offset paginates beyond the first 10 buckets.

Examples:

q=trump days=7
q=trump field=organizations days=7
q="climate change" field=persons language:english days=7

Reference documentation: Segmentation: https://docs.webz.io/docs/webz/news-blogs-forums-segmentation

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "aggregate_webz_news"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	Boolean query with field:value filters. A space means AND; AND, OR and NOT are uppercase. A leading minus also means NOT (tesla -car). Quoted phrases and filter values may contain spaces, for example author:"jane doe". Examples: language:english site:cnn.com country:US. Language values are lowercase full names (hebrew); country values are ISO-2 (GB). Numeric comparisons use > or <, for example domain_rank:<1000. size, sort and days are separate tool arguments.
`days`	No	Lookback in days. Default 7 is the past week. Maximum 31.
`field`	No	Buckets to count. persons is people, organizations is companies. Default persons,organizations runs both. Comma separated.	persons,organizations
`from_offset`	No	Returned pagination offset for non-crawled sorts.
`webz_reporter`	No	When true, include Webz Reporter posts. Default false. This is its own argument. webz_reporter:true inside q does not include those posts.
`include_syndicated`	No	When true, include syndicated copies. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 9, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description discloses real behavioral traits: each field request costs 1 credit, the default field runs two requests, responses cap at 10 buckets, from_offset paginates up to 100 buckets, and older windows get reset to 3 days. That is substantial context the annotations cannot carry, though the 'reset to 3 days' sentence is ambiguous relative to the stated 31-day maximum.

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

Conciseness3/5

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

The core message is front-loaded and the parameter paragraphs are ordered usefully, but the 35-item field enumeration and repeated default values (7 days, false flags) bloat the text without adding decision-relevant information. The days paragraph restates the default and maximum three times and includes a mildly contradictory reset rule.

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

Completeness4/5

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

With no output schema, the description does the needed work of explaining the return shape (buckets with counts, max 10 per response, from_offset up to 100 buckets) and the credit model. It is essentially complete for invocation, with only the days-window reset rule left slightly unclear.

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?

Schema coverage is already 100%, so the baseline is 3, but the description adds meaning the schema does not: 'field' entries are the bucket dimension, the default persons,organizations is literally two billed requests, named site lists are q clauses (custom_sites_list:hot_sites), and webz_reporter is an argument rather than a q filter. The long enumeration of allowed field values largely duplicates schema-level capability rather than adding interpretation.

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

Purpose5/5

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

The opening line states a specific verb and resource ('Count news mentions instead of returning posts (GET /seg_api/news)') and explicitly contrasts the output with a search-style tool, so an agent knows this returns counts, not articles. The follow-up sentence narrows the domain to people/companies mentioned around a topic.

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

Usage Guidelines4/5

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

It tells the agent when this tool applies (entity/topic mention counts on news) and when it does not ('not meaningful on blogs or forums', 'news only'), plus three worked examples with different field values. It stops short of naming any concrete alternative tool for post retrieval, but with no siblings declared the guidance is still clear.

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

All Webz.io News segmentation tools Inspect

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