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mcp-server-and-agent

mcp-server-and-agent

by malcomzww
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

summarise_amounts

Idempotent

Calculate count, total, and mean of amount field for specified record IDs, requiring all IDs to exist.

Instructions

Compute count, total and mean of the amount field across the given record ids. All ids must exist.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "record_ids": "<record_ids>"
    },
    "name": "summarise_amounts"
  }
}

Input Schema

NameRequiredDescriptionDefault
record_idsYeslist of exact record ids

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

The annotations already declare idempotentHint=true and destructiveHint=false, and the description does not contradict them. It adds meaningful behavioral context beyond annotations by stating the precondition that all ids must exist and by naming the calculated summary values, which is especially valuable because no output schema is provided.

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 concise sentences with no filler: the first states the operation and its outputs, and the second states the single relevant precondition. The key information is front-loaded and easy for an agent to parse quickly.

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 simple one-parameter, non-destructive, idempotent aggregation tool, the description is complete: it states what is computed, over which input, and the required precondition. Although there is no output schema, naming count, total, and mean sufficiently describes the return values.

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 coverage is 100% because the input schema already describes record_ids as 'list of exact record ids'. The description adds the role of the ids in the aggregation and mentions the 'amount field', but it does not provide deeper parameter-level detail, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Compute') and identifies the resource ('amount field') and the scope ('given record ids'), clearly distinguishing this as an aggregation tool from the sibling fetch/search/mutation tools. It also enumerates the three outputs (count, total, mean), leaving no ambiguity about what the tool returns.

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?

Usage is implied: an agent can infer this tool is for summarizing amounts across a known set of record ids, and the precondition 'All ids must exist' adds a useful constraint. However, it does not explicitly contrast with alternatives like search_records or fetch_record, nor state when this tool should be preferred over them.

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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