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UK Legislation Changes

search_uk_legislation

Search UK legislation provisions (employment, equality, consumer, data protection, company, health & safety law) by keyword. Returns provisions with their amendment history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 20)
queryYesKeywords, e.g. 'unfair dismissal' or 'disability'

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.2/5.0
Behavior2/5

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

There are no annotations provided, so the description carries the full burden of behavioral disclosure. It mentions that results include amendment history, which is useful, but it does not clarify important behaviors such as jurisdiction scope (UK vs. specific nations), search semantics (exact vs. fuzzy), or whether the tool is an expensive/complex operation. The lack of annotation coverage and minimal behavioral detail leaves significant gaps.

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, with two sentences that pack the core purpose and key output (amendment history). The key verb and resource are front-loaded, and there is no wasted fluff. It is well-structured for quick parsing by an agent.

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

Completeness2/5

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

Given the tool's moderate complexity (legal search), the absence of an output schema and annotations places more burden on the description. It does not explain result structure, pagination (though limit param hints at it), or edge cases like no results or jurisdiction limits. The description is too sparse to fully enable correct invocation in varied contexts, especially since sibling tools deal with amendments and could lead to misuse.

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 input schema already provides 100% coverage of both parameters with examples ('unfair dismissal' or 'disability'), so the baseline is 3. The description adds the context that queries are for legal areas, but it does not add syntax details, advanced query options, or constraints beyond what the schema states. Thus, it barely adds value beyond the schema.

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?

The description clearly states the tool searches UK legislation provisions by keyword and specifies several legal areas (employment, equality, etc.). It also mentions that it returns provisions with amendment history. However, it does not explicitly distinguish itself from sibling tools that deal with amendments, such as get_provision_history or get_recent_amendments, so some ambiguity remains about the unique scope of this tool.

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?

The description implicitly suggests it is for keyword-based searches, but it provides no explicit when-to-use or when-not-to-use guidance. Since siblings handle amendment history, an agent might wonder whether to use this tool for amendment-specific queries or those siblings. There is no mention of alternatives or exclusions, leaving usage context somewhat vague.

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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