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.
| Name | Required | Description | Default |
|---|---|---|---|
| uri | Yes | The URI of the resource to read |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral details beyond annotations: it returns content as a string, and binary content is base64-encoded. This explains the response format for a read operation. It does not mention authentication, rate limits, or error behavior, but with annotations present, the bar is lower and the added context is sufficient.
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 three short sentences, each earning its place. It front-loads the core purpose ('Read a resource by its URI'), then adds needed detail about URI formats and the return format. No filler or redundant repetition with schema or annotations. This is an appropriately sized and well-structured description.
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 tool's simplicity (one parameter, no nested objects) and the existence of an output schema, the description covers everything essential: what the tool does, how to provide the URI for both static and templated resources, and the return format including binary handling. The annotations handle safety and idempotency. No critical gaps remain, making this complete for its context.
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 input schema covers 100% of the parameter description ('The URI of the resource to read'), so the baseline is 3. The description goes beyond the schema by explaining the distinction between static and templated resources, clarifying how to supply the URI in each case. This adds meaningful semantic context that the schema alone does not provide, justifying a score of 4.
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 'Read a resource by its URI,' using a specific verb and resource. It explains static vs templated resources, adding clarity about the tool's scope. However, it does not explicitly differentiate from sibling tools like law_legislation_get_section or law_judgment_get_paragraph, so it misses the 'distinguishes from siblings' criterion for a 5.
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 clear context on how to use the tool: 'For static resources, provide the exact URI. For templated resources, provide the URI with template parameters filled in.' This gives practical guidance but does not state when to use this tool versus alternatives (e.g., when you have a URI from law_list_resources), nor does it mention exclusions. It implies usage a generic resource reader but lacks explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.