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io.ausdata/asic-mcp

io.ausdata/asic-mcp

by Bigred97
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_curated

Lists all curated ASIC dataset IDs that support plain-English filter keys and return aliased, typed columns, helping you pick datasets for filtered queries.

Instructions

List every curated dataset ID in this version of asic-mcp.

These are the datasets where get_data accepts plain-English filter keys and returns aliased, well-typed columns. Each ID is documented via describe_dataset.

Returns: Sorted list of dataset IDs.

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_curated"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.22

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden, and it does add real context: the listing is read-only in nature and the curated IDs are specifically the ones where get_data supports plain-English filter keys and returns aliased, well-typed columns. It also states the return shape is a sorted list. It doesn't cover versioning behavior or what happens if the dataset set changes, hence not a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first sentence, followed by a compact explanation of curated semantics and a short Returns block. All content earns its place, though the line break structure is slightly looser than necessary for such a small tool.

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 no parameters and an output schema present, the description only needs to convey purpose and the meaning of the returned IDs, which it does. The remaining gap is the absence of routing guidance against search_datasets/latest, which is a minor omission for a simple enumeration tool.

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 takes zero parameters, so by rule the baseline is 4. The description correctly reflects a no-argument listing and adds no misleading parameter hints.

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 gives a specific verb and resource — 'List every curated dataset ID in this version of asic-mcp' — and defines what 'curated' means in terms of sibling behavior (get_data accepts plain-English filter keys; IDs are documented via describe_dataset). An agent can distinguish this from search_datasets without opening any schema.

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?

It implies a discovery role by tying curated IDs to get_data and describe_dataset, but never states explicitly when to call this versus search_datasets or latest. No exclusions or prerequisites are given, so usage must be inferred.

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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