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Market and Regulatory Data Feeds — Zinin M2M Hub

by com.timzinin.api

Chotot Vietnam Listings Scraper

chotot-listings
Read-only

Pull live classified ad listings (real estate, vehicles, electronics, jobs and more) straight from Chotot's own public JSON API by region and category. No login, no browser, no proxies. — $0.02/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesOne entry per query, format `region_v2` or `region_v2:cg`. `region_v2` is Chotot's location code (e.g. 13000 = Ho Chi Minh City, 12000 = Hanoi) and `cg` is the category code (e.g. 1000 = real estate, 2000 = vehicles). Codes are visible in the query string of any chotot.com search-results URL. Omit `cg` to pull all categories for that region.
maxConcurrencyNoHow many queries to run in parallel.

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by disclosing that it uses a public API (no login/browser/proxies) and the cost per call ($0.02). This goes beyond the annotations and gives the agent actionable behavioral knowledge.

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: two sentences covering the core function and one key behavioral detail (pricing). Every sentence earns its place with no redundancy or fluff. The pricing line is a useful extra, not a distraction.

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?

The input schema is fully covered, but there is no output schema and the description does not hint at the structure of the returned listings. The agent knows what it gets ('live classified ad listings') but not the fields or format. For a tool with no output schema, a bit more detail on the return value would improve completeness.

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?

Schema description coverage is 100% – both parameters (`items` and `maxConcurrency`) are well-documented in the schema with format, examples, and constraints. The tool description does not add new semantic meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 description uses a specific verb 'Pull' and clearly identifies the resource ('live classified ad listings from Chotot's public JSON API') and the dimensions ('by region and category'). It also distinguishes the tool from siblings by specifying the platform (Chotot Vietnam) and method (no login/browser/proxies).

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 states the tool's scope (Chotot Vietnam, region/category) but does not explicitly tell when to use it versus alternatives. It lacks comparative guidance with sibling tools like `rightmove-london` or `otodom-warsaw`. The scope is implied by the name and description, but no 'when not to use' or alternative suggestions are provided.

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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TDQS

B3.4/5.0
Disambiguation2/5

Many tools have overlapping purposes, with over a dozen real-estate scrapers and half a dozen job boards differentiated only by geography. While descriptions are clear, an agent would struggle to pick the correct tool without prior knowledge of the specific site or region, leading to frequent misselection.

Naming Consistency2/5

Tool names use a mix of lowercase-hyphenated (boss-az, clinical-trials-monitor), underscore (pricing_info), and long descriptive phrases (official-gazette-regulatory-action-router). No consistent verb_noun pattern exists; some start with source domains, others with action nouns. This lack of predictability makes navigation confusing.

Tool Count3/5

36 tools is on the heavy side for a server that could have been more focused. While a 'data hub' can justify many endpoints, the high number of near-identical scrapers (12+ real estate, 6+ job boards) suggests bloat rather than well-scoped functionality. A leaner set with parameterized regional filters would be more appropriate.

Completeness2/5

The claimed domain 'Market and Regulatory Data Feeds' is poorly served: there are no stock/forex/commodity price feeds, few global regulatory sources (only FDA, SEC, EU tenders), and many tools are for job and property listings which are tangential. The set feels like a random aggregation rather than a coherent surface, with obvious gaps for core market and regulatory data.

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