Assign speaker labels to podcast tracks using voiceprints, with dry run enabled by default to preview changes before applying.
Attribute speaker labels across the project from voiceprints (dry_run by default).
| Name | Required | Description | Default |
|---|---|---|---|
| dry_run | No | ||
| project_path | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.1Input schema / properties / project_path / anyOfAdded value: +[
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+]Input schema / properties / project_path / defaultAdded value: +nullInput schema / properties / project_path / typeRemoved value: -"string"Input schema / requiredRemoved value: -[
- "project_path"
-]v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses one important trait – dry_run is on by default, so the operation previews rather than commits – but says nothing about whether existing labels are overwritten, what confidence/scope rules apply, or what permissions are needed.
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?
A single efficient, front-loaded sentence with no filler. The parenthetical is relevant, though slightly redundant with the schema default.
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?
An output schema exists, so return values need not be explained, but for a project-wide mutation tool with no annotations and 0% parameter documentation, the description omits prerequisites, overwrite behavior, and scope details an agent needs to call it correctly.
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?
Schema description coverage is 0%, so the description must compensate. It only restates that dry_run defaults to true (already in the schema's default) and never explains project_path or what its null default means, adding no meaning beyond the structured fields.
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?
States a specific verb (attribute), resource (speaker labels across the project) and mechanism (from voiceprints), which is clearer than most siblings. It does not, however, explicitly distinguish itself from related tools like speaker_label_tool or speaker_enroll_tool, leaving the agent to infer the boundary.
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?
There is no guidance on when to use this tool versus the many other speaker_* siblings, nor any stated prerequisites (e.g. that voiceprints must already be enrolled). The only parenthetical concerns a parameter default, not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.