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mcp-lightcast

mcp-lightcast

by lawwu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

List Classification Releases

list_classification_releases
Read-onlyIdempotent

Lists classifier releases, their removal dates, and supported taxonomy versions, helping you verify which taxonomy releases are available before running classification or extraction tasks.

Instructions

List classifier releases, removal dates, and supported taxonomy versions.

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_classification_releases"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world behavior, so the safety profile is fully covered. The description adds only the content of the listing (releases, removal dates, taxonomy versions) and says nothing about pagination, ordering, or how removal dates should be interpreted (e.g., deprecated vs. upcoming).

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?

A single sentence with no filler, and the resource is stated before the returned fields. Every clause (releases, removal dates, taxonomy versions) adds information.

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 does not need to explain return values, and with no parameters there is little else to cover. The only meaningful gap is the lack of routing guidance among the many sibling metadata/list tools, which the description leaves entirely to the agent.

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 there is no parameter meaning to convey and the baseline of 4 applies. The description correctly avoids inventing filtering options that the empty schema does not support.

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?

The description gives a specific verb ("List") and resource ("classifier releases") and enumerates the payload (removal dates, supported taxonomy versions). It is clearly distinct from mapping/classification tools like list_taxonomy_mappings or classify_occupation, though it never names a sibling to contrast with.

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 only implied: an agent can infer this is the discovery call for available classifier releases and their supported taxonomy versions. There is no explicit statement of when to call it versus get_classification_metadata or get_core_lmi_versions, and no prerequisites or ordering 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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