Skip to main content
Glama

ftg_country_regulations

Read-only

Return import, trade and production regulations for a country — category, title, summary and source. When to use this tool: an agent checks regulatory or compliance requirements before trading or producing in a market. Input: a country, with an optional category.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
limitNo
countryYesCountry ISO code or name
categoryNoOptional regulation category filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
regulationsYes

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already mark it as read-only and open-world. The description restates that it returns data but does not add extra behavioral context like caching, rate limits, or data freshness. No contradiction with annotations.

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 plus a usage line and an input line. Every sentence serves a distinct purpose—describing output, usage context, and input parameters. No wasted words.

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 that an output schema exists (per context signals) and the tool is a straightforward read-only lookup, the description provides enough context for an agent to understand its role. It could mention what happens when no regulations are found, but the output schema likely handles that.

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?

The description explicitly says 'Input: a country, with an optional category,' which adds value by making the optionality clear beyond the schema's property descriptions. However, it does not cover optional 'async' or 'limit' parameters, though these are common patterns and documented in the schema.

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 clearly states it returns import, trade, and production regulations for a country, listing specific fields (category, title, summary, source). This distinguishes it from the many sibling tools that deal with other aspects of trade, compliance, or country data.

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 includes a 'When to use' statement that gives context (regulatory/compliance checks before trading/producing), but it does not explicitly mention when not to use it or point to alternative tools for related but distinct tasks (e.g., sanctions screening, trade finance eligibility).

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.5/5.0
Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources