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Glama

bank_recommendation

Read-onlyIdempotent

Recommends UAE business banks by industry, minimum balance budget, and onboarding speed, filtering for digital, traditional, or international tiers and flagging high-risk sectors.

Instructions

Recommend UAE business banks based on industry, minimum balance budget, and onboarding speed.

Input Schema

NameRequiredDescriptionDefault
tierNoOptional filter, one of "digital", "traditional", "international".
limitNoMaximum results (1 to 20, default 5).
industryNoBusiness industry category. Crypto, forex, jewelry, used cars, and money service businesses are auto-flagged as high risk.general
is_high_riskNoForce the high-risk warning even if industry is not in the auto-list.
speed_priorityNoTrue if onboarding speed matters more than min balance (favours digital banks).
budget_min_balance_aedNoMaximum minimum-balance the founder can accept (filters out banks above this).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the ranking dimensions but nothing beyond the schema, and does not note behaviors such as how high-risk flagging affects results. With annotations carrying the behavioral burden, a 3 is appropriate.

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

Conciseness4/5

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

A single, front-loaded sentence with no padding. It is efficient, though it is arguably too terse for a six-parameter recommendation tool and leaves room for a clause on scope or output.

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?

An output schema and rich annotations are present, so return values and safety need not be described. Still, for a recommendation tool with six optional parameters and no required inputs, the description leaves the agent to infer call behavior and ranking logic entirely from the schema.

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 all six parameters (tier, limit, industry, is_high_risk, speed_priority, budget_min_balance_aed) are already documented in the schema. The description names three related concepts but adds no syntax or filtering nuance beyond what the schema provides, so the baseline 3 is correct.

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?

States a specific verb (Recommend) and resource (UAE business banks) plus the ranking factors (industry, minimum balance budget, onboarding speed). This reasonably distinguishes it from siblings list_banks and bank_details, though it does not explicitly name them.

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?

Usage is implied by 'recommend ... based on' – the agent can infer it should be used when seeking a ranked shortlist rather than raw listings. However there is no explicit when-to-use vs when-not, and no mention of list_banks/bank_details as alternatives for comparison.

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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