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UK Business Tools - Ledgerhall

Check MTD VAT Status

law_hmrc_check_mtd_status
Read-onlyIdempotent

USE THIS TOOL WHEN you have a 9-digit VAT Registration Number and need that business's Making Tax Digital VAT mandate status.

Returns whether the business is mandated for MTD, effective date, and trading name.

Connects to the HMRC sandbox by default. Set HMRC_API_BASE to 'https://api.service.hmrc.gov.uk' for production. Requires HMRC_CLIENT_ID + HMRC_CLIENT_SECRET environment variables (OAuth 2.0). Raises if credentials are not configured — do not infer status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vrnYesVAT Registration Number: 9 digits, e.g. '123456789'. GB prefix accepted and stripped automatically.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
vrnYesVAT Registration Number queried
mandatedYesWhether this business is mandated for MTD VAT
trading_nameNoRegistered trading name if available
effective_dateNoDate from which MTD obligation applies

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the read-only and idempotent hints in annotations, the description adds crucial operational context: the default to HMRC sandbox, the production URL via HMRC_API_BASE, and the need for HMRC_CLIENT_ID/SECRET credentials. It also discloses that the tool raises an error if credentials are missing, and explicitly warns not to infer status. This is exactly the kind of behavioral detail that annotations don't capture.

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 concise and front-loaded, with the most important 'when to use' statement first. It covers purpose, return values, and setup in just a few lines without redundancy.

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

Completeness5/5

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

For a simple one-parameter read-only tool with an output schema and annotations, this description covers all essential aspects: trigger condition, return fields, environment configuration, and error behavior. The existence of an output schema means detailed return-value structure need not be in the description.

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 mentions the VRN and its format in the trigger sentence, but the schema itself already provides full coverage with min/max lengths, an example, and the note about GB prefix stripping. No additional parameter meaning is added beyond the schema, so the baseline score for high coverage applies.

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 opens with an explicit trigger: 'USE THIS TOOL WHEN you have a 9-digit VAT Registration Number and need that business's Making Tax Digital VAT mandate status.' This clearly specifies the verb (check), the resource (MTD VAT status), and the starting condition. It distinguishes from sibling VAT tools such as law_hmrc_get_vat_rate which handles rates, not mandate status.

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

Usage Guidelines4/5

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

The tool is explicitly scoped to a scenario involving a VRN and the MTD mandate status. It also states environment and credential prerequisites, implying that this tool is not usable without proper configuration. However, it doesn't explicitly name alternate tools to use instead in other scenarios, so it falls just short of full guidance.

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

A4/5.0
Disambiguation4/5

Tools are well-grouped by domain prefixes (dd_, gov_, law_, prop_) with clear descriptions that differentiate them. However, there is minor overlap, e.g., dd_search could be used instead of individual searches, and dd_fetch versus dedicated profile tools might cause confusion.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with domain-specific prefixes (dd_, gov_, law_, prop_). Names are descriptive and predictable, e.g., dd_charity_search, gov_govuk_search, law_bills_search_bills.

Tool Count4/5

70 tools is high but justified by the broad scope covering due diligence, government, legal, and property domains. Each domain has a reasonable number of tools (about 15-20 each). The count is on the upper end but still manageable.

Completeness5/5

The tool set is comprehensive across all domains: full CRUD for companies and charities, detailed legal research (cases, legislation, parliament, citations), property data (EPC, planning, price paid, rentals), and government information. No obvious gaps for the intended use cases.

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