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UK Data for Agents

package_info

Latest version, publish date, deprecation, licences, advisories and links for a package (deps.dev). (cost: 1 credit)

Input Schema

NameRequiredDescriptionDefault
nameNostring, required
ecosystemNonpm|pypi|cargo|go|maven|nuget|rubygems

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full behavioral burden but does disclose two useful facts: the upstream source (deps.dev) and the cost (1 credit). It is silent on whether the call is read-only, what happens for an unknown package name, whether a 404 is returned or an empty result, and any rate limiting — gaps that matter for unannotated tools.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single tight sentence, front-loaded with the most salient output field and ending with source and cost. No filler. It would read slightly better as a verb phrase ('Get latest version …') to make the action explicit, but nothing is wasted.

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

Completeness3/5

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

For a 2-parameter lookup with no output schema, the enumeration of return fields is genuinely useful as a de-facto output description. However, required-parameter semantics remain ambiguous (schema declares zero required while 'name' is annotated 'string, required'), and failure behavior for unknown packages is unaddressed, leaving the definition under-complete for its simplicity level.

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%, so both parameters are documented in the schema, including the ecosystem value set (npm|pypi|cargo|go|maven|nuget|rubygems). The description adds nothing about parameter meaning, default ecosystem behavior, or whether name must be qualified — baseline 3 is the correct ceiling given the schema already does the work.

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 names the exact resource ('a package') and enumerates the fields returned (latest version, publish date, deprecation, licences, advisories, links), plus the data source (deps.dev). An agent knows immediately this is a package metadata lookup. It falls short of 5 because it never distinguishes itself from adjacent siblings such as vuln_check, which also covers advisories.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance, and no named alternative is offered for overlapping needs (e.g. vuln_check for security-only queries, product_recalls for a different domain). Usage is only inferable from the field list, which is weaker than explicit routing 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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