Bizfile MCP

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

With no annotations, the description carries the full burden. It discloses data sources (386 sources via OpenSanctions), update frequency, and return verdict format. It does not explicitly state it is non-mutating, but the verb 'checks' and 'screens' clearly imply a read-only operation.

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?

Despite length, every sentence earns its place: purpose, usage ordering, legal mandates, data sources, and return values are all covered without redundancy. It is front-loaded with the core function and maintains a clear flow.

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?

Given the output schema exists, the description still explains return values directly. It covers preconditions (after validate_counterparty), all relevant use cases, compliance specifics, and operational consequences. No critical context is missing for correct invocation.

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 coverage is 100%, providing a baseline of 3. The description adds valuable guidance on the 'officers' parameter, specifying it should come from validate_counterparty's response, and mentions the 'country' parameter for narrow search. This goes beyond schema text.

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 opens with a specific verb and resource: 'Checks counterparty sanctions status.' It clearly distinguishes from siblings by stating it is a follow-up to validate_counterparty, focusing on sanctions screening rather than general counterparty validation.

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?

Explicit sequencing is given: 'Call this BEFORE invoking any agentic payment rail -- immediately after validate_counterparty.' It also lists concrete use cases (e.g., e-invoicing mandates) and specifies when to prefer it over other tools.

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, the description carries the full burden. It discloses the validation method (UK Companies House + AI risk scoring), the output verdict, and important consequences of non-use (no chargeback, rejected e-invoices). It does not mention authentication/rate limits but provides meaningful behavioral context.

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 thorough but lengthy (~200 words). It front-loads purpose and usage, but includes extended risk explanations and regulatory deadlines that, while useful, could be more concise. Still organized into logical sections.

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?

Description covers usage context, regulatory timelines, consequences, and next steps (screen_counterparty). Since an output schema exists, return values are covered. Minor gap: it claims validation for EU/UK/AU suppliers but only mentions UK Companies House, which could confuse cross-region validity.

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% with clear parameter explanations. The description adds no new parameter-level semantics beyond the schema, so the baseline 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?

Description clearly states the tool 'validates counterparty legitimacy' and specifies the exact use case before agentic payment rails or e-invoicing onboarding. It distinguishes from siblings by naming the next step (pass to screen_counterparty) and implies validate_counterparty_lite is a lighter alternative.

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?

Provides explicit 'when to use' instructions: before invoking any agentic payment rail and before onboarding EU/UK/AU suppliers into e-invoicing workflows. It lacks explicit alternatives comparison or 'when not to use' guidance, but the context is strong.

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, the description carries the behavioral burden. It discloses that the tool returns registry status in under 1 second, performs no AI/officer/risk analysis, and produces a machine-readable status field. It also warns about the consequences of dissolved entities, adding useful context. It does not mention side effects or whether it is strictly read-only, but the read-like nature is implied.

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 relatively long and includes a lengthy motivational warning about Stripe MPP, Alipay AI Pay, and Shopify UCP exposure. While this context is somewhat useful, it could be trimmed without losing essential guidance. The core instructions are present but not as tightly packaged as the high-scoring examples.

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?

An output schema exists, so return values are covered. The description explains when to use the tool, what it returns, and the next step (validate_counterparty for non-ACTIVE results). It is sufficiently complete for a simple lookup tool, though it does not mention edge cases like not-found behavior.

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 covers both parameters (company_name and company_number) with clear descriptions, so the description adds no additional parameter semantics. Baseline of 3 is appropriate since schema coverage is 100%.

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 it validates counterparty registry status and emphasizes it's a fast, lite check without AI, officers, or risk score, distinguishing it from the heavier validate_counterparty. However, the exact relationship to screen_counterparty is not fully clarified, and the phrasing 'before pre-screening' is slightly ambiguous.

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 explicit usage context: use for high-volume batches needing a fast registry check before full validation, and it explicitly instructs to call validate_counterparty on non-ACTIVE results. It does not directly address when to use screen_counterparty instead, but the workflow guidance is otherwise clear.

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