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cw_note_edit_help

Explains how to edit notes through the quantization dialog when automation cannot read them, covering field labels, common mistakes, and verification steps.

Instructions

How note-level editing actually works: notes cannot be READ through any automation surface, but they can be EDITED through the dialog behind 处理 > 量化, and the exported .mid file is what proves it. Carries the measured field labels, the two mistakes that produced wrong conclusions, and the full verification round trip.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose the important behavioral facts: this is informational content, it names the concrete UI path (处理 > 量化 dialog), and it warns that omitting it previously produced wrong conclusions. It stops short of saying the output is prose documentation, which keeps it from 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.

Conciseness3/5

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

It is a single dense sentence with no wasted clause, but the lead is content ('How note-level editing actually works') rather than a front-loaded statement of purpose and return value. Phrases like 'is what proves it' and 'actually' add rhetoric without 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?

No output schema exists, so the description must signal what comes back, and it enumerates the payload (measured field labels, two documented mistakes, full verification round trip). That is sufficient for a zero-parameter knowledge tool, though stating explicitly that it returns reference text would close the gap.

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, so the baseline is 4; there is nothing for the description to disambiguate. No credit above baseline since it adds no parameter guidance beyond what the empty schema already conveys.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description conveys the topic (note-level editing behavior, including the fact that notes cannot be read by automation) but never states the tool's action or return type — an agent must infer it is a help/knowledge article rather than an editing operation. It does distinguish itself from cw_get_notes by declaring notes are unreadable through automation, but the verb+resource framing is absent.

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 implied: consult this when you need to understand or verify note-level editing, and the line about notes being unreadable steers the agent away from read-oriented siblings like cw_get_notes. There is no explicit 'call before attempting X' or named alternative, so the routing signal is indirect.

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