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Market and Regulatory Data Feeds — Zinin M2M Hub

FDA Approval Feed

fda-approval-feed
Read-only

Watch drugs or companies for new FDA approvals and recalls. Official openFDA data, free, no API key or login. Get application status, sponsor, latest submission and recall details for every match. — $0.02/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to pull per query, per source (approvals/recalls).
datasetNoWhich openFDA feed to check.both
queriesYesDrug or company names to watch (e.g. `pembrolizumab`, `Pfizer`, `semaglutide`). One row per query.
maxConcurrencyNoHow many queries to process in parallel.

TDQS

A4/5.0
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 safety profile is covered. The description adds valuable behavioral context: free and no login required, official openFDA data, and cost ($0.02/call in USDC on Base). This goes beyond the annotations by disclosing pricing and authentication requirements.

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: three sentences plus a cost note. It front-loads the core purpose ('Watch drugs or companies...') and wastes no words. Every sentence provides essential information (what it does, data source, return details, cost).

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 the absence of an output schema and the tool's moderate complexity (4 parameters with full schema coverage), the description adequately covers the tool's capabilities. It details the types of information returned (application status, sponsor, latest submission, recall details) and adds pricing. However, it lacks guidance on how the 'watch' behavior works (e.g., polling frequency, whether results are incremental) and doesn't mention potential rate limits or pagination.

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 coverage is 100% with all parameters having descriptions. The tool description does not add any additional meaning beyond what the schema already provides for parameters like `queries`, `limit`, `dataset`, or `maxConcurrency`. Baseline score of 3 is appropriate since the description adds no value here.

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 starts with a specific verb ('watch') and clearly identifies the resource (drugs or companies for FDA approvals and recalls). It distinguishes from sibling tools like clinical-trials-monitor by focusing on FDA regulatory actions rather than clinical trials. The scope (new approvals and recalls) and data source (openFDA) are explicit.

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 implies usage for monitoring FDA approvals and recalls but provides no explicit guidance on when to use this tool versus alternatives (e.g., clinical-trials-monitor for clinical trial data, or sec-edgar-watcher for SEC filings). It also doesn't mention when not to use it.

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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