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paulieb89

UK Legal Research MCP Server

read_resource

Read-only

Access UK legal documents by URI to retrieve case law, legislation, parliamentary debates, or tax guidance content for research and analysis.

Instructions

Read a resource by its URI.

For static resources, provide the exact URI. For templated resources, provide the URI with template parameters filled in.

Returns the resource content as a string. Binary content is base64-encoded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uriYesThe URI of the resource to read

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations provide readOnlyHint=true, which the description doesn't contradict. The description adds valuable behavioral context beyond annotations: it specifies return format ('resource content as a string'), handling of binary content ('base64-encoded'), and distinguishes between static vs templated resource handling. This provides practical implementation details not captured in annotations.

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 perfectly concise with three focused sentences: purpose statement, URI format guidance, and return value specification. Every sentence adds essential information with zero waste. The structure is front-loaded with the core purpose followed by implementation details.

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

Completeness4/5

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

Given the tool has annotations (readOnlyHint), 100% schema coverage, and an output schema exists (though not shown), the description provides good contextual completeness. It covers purpose, input handling nuances, and return format. The main gap is lack of explicit differentiation from sibling tools, but overall it's quite complete for a simple read operation.

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 description coverage is 100% with the single 'uri' parameter well-documented. The description adds some context about URI types (static vs templated) but doesn't provide additional semantic meaning beyond what the schema already states. With complete schema coverage, the baseline score of 3 is appropriate as the description adds minimal extra parameter information.

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's purpose with 'Read a resource by its URI' - a specific verb (read) and resource (resource by URI). It distinguishes from siblings like 'list_resources' by focusing on individual resource retrieval rather than listing. However, it doesn't explicitly contrast with other read-like siblings such as 'bills_get_bill' or 'legislation_get_section'.

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 provides some usage context by distinguishing between static and templated resources, but doesn't explicitly state when to use this tool versus sibling tools like 'list_resources' or other get/read operations. It offers technical guidance on URI format but lacks explicit when/when-not guidance relative to alternatives.

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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