Market and Regulatory Data Feeds — Zinin M2M Hub

Gov Tender Radar

gov-tender-radar

Read-only

Search EU public-sector tenders (TED Europa) by keyword or CPV code, optionally filtered by buyer country. Returns tender title, buyer, country, CPV codes, deadline and notice URL. No API key, no browser — public TED search API only. — $0.02/call, x402 (USDC on base).

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Max number of notices to return per query.
`country`	No	ISO 3-letter buyer-country code to AND into every query, e.g. "DEU", "FRA". Leave empty for all EU countries.
`queries`	Yes	Keywords or TED expert-query expressions, one search per entry. Plain words (e.g. "software") do a full-text search; field expressions (e.g. "classification-cpv=72000000") filter directly; mix both with AND/OR (e.g. "cloud AND classification-cpv=72*").
`maxConcurrency`	No	How many queries to run in parallel against TED.

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by noting 'No API key, no browser — public TED search API only' and the cost ($0.02/call, x402 USDC). No contradictions with annotations. It could mention rate limits or result ordering, but overall it enriches the behavioral profile.

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 three sentences, each with distinct purpose: purpose + returns, ease of use, cost. Front-loaded, no wasted words, and easy to parse. Perfectly concise for the tool's complexity.

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?

Given 4 parameters with 100% schema coverage, no output schema, and no nested objects, the description effectively covers the tool's purpose, return fields, key constraints, and cost. It could add details about result ordering or pagination, but the overall picture is complete enough for an agent to use the tool correctly.

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%, so baseline is 3. The description reinforces the schema by mentioning 'keyword or CPV code' (mapping to queries) and 'filtered by buyer country' (mapping to country). It does not add new syntactic or semantic details beyond the schema's own descriptions.

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 searches EU public-sector tenders on TED Europa by keyword or CPV code, with optional country filter. It specifies the return fields (title, buyer, country, etc.). However, it does not explicitly differentiate from sibling tools like 'tender-alert' or 'uk-public-tender-lead-alert', leaving the agent to infer scope differences.

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 context (EU tenders, public TED API, no auth) but does not explicitly state when to use this tool vs. alternatives. Usage is implied by the scope 'EU public-sector tenders', but no when-not guidance or sibling tool comparisons are given.

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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