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List droplets

list_droplets
Read-onlyIdempotent

List Droppy's droplets: the extensions built into Droppy and the ones in the Droplet Store, with a summary and documentation link for each. Filter by text or by kind.

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": "list_droplets"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindNoOnly built-in droplets, or only Droplet Store droplets.
queryNoOnly droplets whose name, id or summary contains this text.

Output Schema

NameRequiredDescriptionDefault
totalYes
dropletsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered in structured data. The description adds that each entry carries a summary and documentation link, which is modest beyond what the output schema likely already conveys, and it says nothing about result volume, ordering, or pagination limits for a list endpoint.

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?

Two short sentences with no filler: the resource and its scope come first, then the return content, then the filtering options. Every clause carries information an agent can act on.

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?

With an output schema present, the description needn't explain return values, and annotations cover the safety profile; what remains is a clear statement of scope and filtering. The only notable omission is any hint about result size or ordering, which matters for a listing tool but is a minor gap here.

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%, with both the kind enum and the query field fully documented in the schema itself, so the baseline is 3. The description's "filter by text or by kind" merely restates the two parameters without adding matching semantics (e.g., case sensitivity or whether query hits id, name, or summary) beyond what the schema states.

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?

"List Droppy's droplets" gives a specific verb and resource, and the follow-up clause defines what a droplet is (built-in extensions plus Droplet Store items) so an agent doesn't need prior domain knowledge. It stops short of naming how it differs from siblings like fetch_droppy_page or search_droppy_docs, leaving that distinction to be inferred from the verbs.

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?

"Filter by text or by kind" implies when the optional parameters are useful, giving partial usage context. There is no explicit guidance on when to choose this listing over search_droppy_docs or fetch_droppy_page, and no stated exclusions or prerequisites.

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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