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by com.llclane
OverviewDiscussionsAdmin

Where this data comes from, and how to cite it

dataset_provenance

The source, the date it was computed, the licence and the citation for the LLC Lane dataset. Read this to attribute a figure correctly.

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": "dataset_provenance"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It discloses what fields will be returned (source, date, licence, citation) but does not explicitly state that the operation is read-only or describe any errors or side effects. 'Read this' hints at read-only behavior, but transparency is partial.

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 sentences, no filler, and the key content is front-loaded. The description is minimally sized while still conveying content and intended use.

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 0-parameter metadata look-up, the description gives all essential context: the dataset, the fields included, and the reason to call it. It could explicitly mention that no inputs are required, but the schema already makes that obvious, so the omission is minor.

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, and the empty schema already communicates this. The description adds no parameter-specific guidance, but none is needed; the 0-param case receives a baseline of 4.

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 identifies the resource (LLC Lane dataset) and the specific payload (source, computed date, licence, citation). The closing instruction 'Read this to attribute a figure correctly' states the purpose and differentiates it from sibling tools like dataset_columns or dataset_stats.

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

Usage Guidelines4/5

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

It explicitly tells the agent when to invoke the tool: whenever attribution is needed. It doesn't list exclusions or alternatives, but the domain of provenance is so distinct from the sibling dataset tools that an agent can reliably route based on the stated purpose.

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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