Bancadia MCP

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

With no annotations, the description carries the full behavioral disclosure burden. It explains that tier-specific fees/features are nested under plan_tiers whereas general ones are top-level, and that certain details are not returned by the sibling tool. It does not discuss auth or side effects, but the read-only nature is strongly implied by 'Get' and the detail-oriented purpose.

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

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

Two moderately dense sentences, front-loaded with the core purpose. Each clause adds meaningful context—excluded fields, tier nesting, follow-up usage—though the long parenthetical around gotcha fees makes the opening sentence somewhat heavy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, the description sufficiently explains what is returned (fees, features, tier nesting) and how it differs from the sibling tool. The agent has enough context to decide when to invoke this tool and what to expect from the response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description reinforces that the slug should come from query_business_checking results and must not be an internal database id, but it adds little beyond the schema's own parameter description. No new parameter semantics are introduced.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Get full detail') and a specific resource ('one specific business checking listing'), and explicitly contrasts it with query_business_checking's broad list. It clearly distinguishes the tool from its sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to use this as a follow-up after query_business_checking and names the alternative tool. It also identifies the trigger: when the caller has already identified one listing by slug, implying when not to use it (for broad list results).

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that only active and verified listings are returned, and that the soft-ranking parameters do not exclude non-matching listings but only lower their rank. This is meaningful behavioral context beyond what the schema provides.

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

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

The description is two sentences long and front-loaded with the core purpose. The second sentence explains the notable soft-ranking behavior without unnecessary detail. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main query behavior, return scope (active/verified), and optional ranking behavior. With 17 parameters and full schema coverage, the description complements the schema well, though it does not mention pagination or default behavior when no filters are provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents all parameters with 100% coverage, including the soft-ranking semantics for target_industries and target_business_profiles. The tool description adds no parameter-specific details beyond the overall context, 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries a registry for business checking products using compound filter criteria, and specifies it returns active, verified listings. This distinguishes it from the sibling get_business_checking_listing, which likely retrieves a single listing rather than querying a set.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool (querying with filters) and explicitly describes the optional soft-ranking behavior, including that non-matching listings are still returned. It does not explicitly contrast with the sibling tool, but the context is unambiguous.

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