Skip to main content
Glama
netease-music-mcp
by xinyu68

netease_like

Like or unlike a song with a true/false flag, defaulting to the current song when no ID is provided and verifying the change by reading it back.

Instructions

按明确意图喜欢或取消喜欢歌曲;liked为true/false,省略songId时使用当前歌曲,写入后读回验证

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "requestId": "<requestId>",
      "liked": "<liked>"
    },
    "name": "netease_like"
  }
}

Input Schema

NameRequiredDescriptionDefault
likedYes
songIdNo
requestIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A3.6/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true), it discloses two non-obvious behaviors: the operation is an explicit set of liked=true/false (idempotent, not a blind toggle) and the write is read back to verify before returning. It adds no auth or rate-limit context, and the meaning of the verification result is unstated.

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?

A single dense sentence with the action front-loaded and clarifications appended as semicolon clauses; nothing is redundant. It is somewhat telegraphic, which costs a little readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutating tool with no output schema and 0% schema coverage, the description covers state semantics and the verification readback but leaves requestId (presumably an idempotency key) and the verification outcome undefined. An agent can call it, but not fully predict its behavior or result.

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 0%, so the description must carry the load: it explains liked (true=like, false=unlike) and songId (omitted = current song), which is real added meaning. The third parameter, requestId, is never explained, so roughly a third of the parameters remain undocumented in both schema and description.

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?

States a concrete verb pair (like/unlike a song) with the exact state parameter, and '按明确意图' signals an explicit-state operation rather than a blind toggle. It does not explicitly name netease_liked_songs as the read-side sibling, so sibling differentiation is implied rather than stated.

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 clarifies when to omit songId (fall back to the currently playing song) and that intent must be explicit, which is useful invocation guidance. However, it never says when not to use this tool or points to netease_liked_songs for reading like state, so usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.