How licensing works: one-time licences, subscriptions, what covers films/TV/streaming, YouTube Content ID claims and channel whitelisting.
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": "licensing_info"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implicitly signals a read-only informational lookup with no side effects and no inputs, which is the main behavioral fact. However it never states the shape of the response (FAQ text, structured rules, examples) or that the content is static reference material rather than account-specific.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no filler, and the topic list is front-loaded after the framing clause 'How licensing works'. It is a sentence fragment rather than a full statement of what the tool does, but nothing in it is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter reference tool with no output schema and no annotations, the description covers the important ground: the domain and the specific subtopics an agent can expect answered. The only real gap is that the return format is unspecified, which matters little here since there is nothing to invoke incorrectly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The enumerated topic list does usefully tell the agent what subject matter the (parameterless) response will span.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the resource (licensing) and enumerates the specific subject areas covered: one-time licences, subscriptions, film/TV/streaming coverage, YouTube Content ID claims, and channel whitelisting. That makes it unmistakably a reference/knowledge tool rather than an action on the music catalog, distinguishing it from siblings like get_track and search_music. It stops short of explicitly saying it returns explanatory documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: call this when you need to understand licensing terms. There is no explicit when-to-use statement, no mention of what it does not answer, and no named alternative. Given the zero-parameter reference nature of the tool the risk is low, but guidance is inferred rather than stated.
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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