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Buying decisions across this organisation's farms

eudr_procurement_overview
Read-onlyIdempotent

List the organisation's farms and its recent buying decisions (GO / GO WITH CONDITIONS / NEEDS A PERSON / NO-GO per destination), with which carry a recorded outcome and which were overridden. Use it to find a farm id before eudr_decide_lot, or to see how decisions have turned out. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
farmsYes
countsYes
decisionsYes
lot_exampleYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / lot_example
      Added value: +{
      +  "type": "object"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "decisions",
      -  "counts",
      -  "farms"
      -]New value: +[
      +  "decisions",
      +  "counts",
      +  "farms",
      +  "lot_example"
      +]
  2. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds behavioral context by specifying the scope ('across this organisation's farms'), the decision statuses included, and the fact that it includes both recorded outcomes and overridden decisions. It doesn't describe pagination or return format, but the output schema exists and the description is otherwise transparent.

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?

Three sentences, front-loaded with the core listing purpose, then the decision statuses, then the use cases. Every sentence earns its place; no fluff or repetition of the title.

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

Completeness5/5

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

For a zero-parameter read-only tool with an output schema, the description is complete. It tells the agent what data is returned, how to use it (find farm id, review outcomes), and that it is safe to call. Nothing essential is missing.

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?

The tool has zero parameters, so the schema is trivially complete. The description adds meaning by explaining what the returned data represents (farms and buying decisions with statuses), which is more than the empty schema provides. Baseline for 0 params is 4, and the description earns it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists the organisation's farms and recent buying decisions with specific decision outcomes (GO / GO WITH CONDITIONS / NEEDS A PERSON / NO-GO), and notes which have recorded outcomes and which were overridden. It distinguishes itself from siblings by naming eudr_decide_lot as a follow-up use case.

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

Usage Guidelines5/5

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

The description explicitly says when to use it: to find a farm id before eudr_decide_lot, or to see how decisions have turned out. It also states it is read-only, which helps an agent avoid using it for mutation purposes. It doesn't explicitly name alternatives to avoid, but the use cases are clear enough.

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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