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DAITK (Dibblee AI Tool Kit) - Total Import Cost

recent_changes

What changed since a given date (YYYY-MM-DD, default today): newly-touched trade measures and newly-detected amendments. Good for a daily 'what did the government change today' digest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the default value of the 'since' parameter and the result categories, which is helpful. However, it does not explicitly state that this is a read-only query, nor does it mention ordering, pagination, inclusivity of the date, or any access requirements.

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 with no wasted words. The first sentence states the tool's function and parameter details; the second gives a concrete use case. Information is front-loaded and easy to parse quickly.

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?

For a simple one-parameter read tool with no output schema, the description covers the essential points: what it returns, how to specify the date, the default, and a typical use case. Minor gaps like exact return structure and date boundary semantics exist, but they are not critical for the intended digest use case.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates well for the only parameter by specifying the expected format (YYYY-MM-DD) and the default value (today). This gives an agent the meaningful semantic context that the bare 'type: string' schema lacks.

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 identifies a time-bounded query over trade measures and amendments, specifying what it covers: 'newly-touched trade measures and newly-detected amendments.' It is distinct from the sibling detail/lookup tools by its focus on changes over time, though it could have been stronger with an explicit verb like 'list' or 'get recent changes.'

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 phrase 'Good for a daily what did the government change today digest' provides a concrete use case, so an agent can infer when to use it. However, there is no explicit guidance on when not to use it in favor of siblings such as list_trade_measures or get_measure_detail, so the usage guidance remains implied rather than explicit.

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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