UK Business Tools - Ledgerhall

Get GOV.UK Organisation

gov_govuk_get_organisation

Read-onlyIdempotent

Get the profile of a UK government organisation by its slug.

Returns name, acronym, type, status, web URL, and parent/child organisations. Use govuk_list_organisations to browse all organisations and discover slugs.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes	Organisation slug, e.g. 'hm-revenue-customs'. Find slugs via govuk_list_organisations.

Output Schema

TableJSON Schema

Name	Required	Description
`slug`	No	Organisation slug, e.g. 'hm-revenue-customs'. Usable with govuk_search filters.
`type`	No	Organisation type, e.g. 'ministerial_department', 'executive_agency', 'non_ministerial_department', 'public_corporation'.
`state`	No	GOV.UK status, e.g. 'live', 'closed', 'transitioning'.
`title`	No	Full organisation title.
`acronym`	No	Organisation acronym, if set.
`web_url`	No	Absolute https://www.gov.uk URL for the organisation page.
`contact_details`	No	Contact details block from GOV.UK (phone, email, address) when available.
`child_organisations`	No	Titles of child organisations / agencies under this body.
`parent_organisations`	No	Titles of parent organisations this body reports into.

TDQS

A4.3/5.0

Behavior3/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds a list of returned fields, but an output schema exists, so this is redundant. It provides no additional behavioral context beyond what annotations and schema already convey.

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 two sentences: the first states the core function, the second lists return fields and points to the sibling for slug discovery. Every sentence earns its place; no fluff.

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 one-parameter, read-only tool with both input and output schemas, the description is complete. It covers what the tool does, what it returns, and how to obtain valid input (slugs). No significant gaps remain.

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 coverage is 100% and the parameter description already includes an example ('hm-revenue-customs') and a pointer to govuk_list_organisations for finding slugs. The tool description's mention of 'slug' and 'discover slugs' merely repeats schema content, adding no new semantic value.

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 states a specific verb ('Get') and resource ('profile of a UK government organisation by its slug'), immediately distinguishing it from list-style siblings like govuk_list_organisations. It also lists return fields, making the tool's function unmistakable.

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

Usage Guidelines5/5

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

Explicitly instructs to use govuk_list_organisations for browsing/discovering slugs, which tells the agent when NOT to use this tool. This clear alternative makes the usage context unambiguous.

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.

Resources

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