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tea-planner

tea-planner

by blyatman996
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

inventory

List tea stock and brewing parameters, filterable by category such as green, oolong, or black tea.

Instructions

列出库存茶品及壶泡参数。category 可选：绿茶/调味绿茶/花茶/白茶/黄茶/乌龙茶/红茶/调味红茶/黑茶/代用茶。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "inventory"
  }
}

Input Schema

NameRequiredDescriptionDefault
categoryNo

Output Schema

NameRequiredDescriptionDefault
resultYes

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?

With no annotations provided, the description must carry the behavioral burden. The verb 列出 clearly signals a read-only query operation and names what is returned, which is sufficient for a simple list tool. It does not explicitly discuss ordering, pagination, or live-vs-snapshot semantics, but these are minor for this low-complexity operation.

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 one compact sentence that front-loads the action and resource, then adds the only parameter information an agent needs. Every clause contributes; there is no filler.

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 one-parameter list operation with an output schema, the description covers the core behavior and filter values completely. It stops just short of full completeness by not explicitly stating that an omitted category returns all items and by not framing when inventory should be preferred over sibling tools.

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

Parameters5/5

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

The input schema provides only a bare string with an empty default and no enum, while the tool description supplies the full parameter meaning: category is an optional filter and all ten accepted values are enumerated. This fully compensates for the 0% schema description coverage.

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 opens with the explicit verb 列出 and names the exact resource 库存茶品及壶泡参数, making the tool's function unmistakable. This also separates it from mutation siblings like add_tea, remove_tea, and clear_inventory, which clearly imply write operations rather than listing.

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?

No guidance is given about when to choose inventory over siblings such as history, recommend, or coldbrew_recommend, and no exclusions or alternative conditions are stated. The only usage hint is the optional category filter, which is parameter-level guidance rather than tool-selection 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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