Score an existing or proposed podcast cut join to detect clicks and glitches before finalizing edits.
Score an existing or proposed cut join for audibility artifacts (clicks, glitches).
| Name | Required | Description | Default |
|---|---|---|---|
| cut_end | No | ||
| speaker | No | ||
| join_sec | No | ||
| timebase | No | timeline | |
| track_id | No | ||
| cut_start | 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. 'Score' implies a non-mutating read, but the description never confirms this, nor does it mention permissions, cost, or whether it can be run on uncompiled edits. For a 7-parameter tool with zero annotation coverage, this is a thin disclosure.
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 front-loaded sentence with no waste, and the parenthetical sharpens what 'artifacts' means. Efficient, though arguably too terse for a tool with seven opaque parameters.
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 described, but with 7 undocumented optional parameters, no annotations, and no required fields, the agent is left guessing how to specify which join to score. The definition is incomplete for a tool of this parameter complexity.
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?
Seven parameters (cut_start, cut_end, join_sec, track_id, speaker, timebase, project_path) have 0% schema description coverage and the description adds no meaning whatsoever about how to identify or scope a join. It does not even hint whether a join is located by time, track, or speaker.
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 ('score'), a specific resource ('cut join'), and the dimension being evaluated ('audibility artifacts (clicks, glitches)'), so an agent knows exactly what the tool returns. However, it does not distinguish itself from related join siblings like join_qa_sweep_tool or join_label_tool, which likely also operate on joins.
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?
'existing or proposed cut join' hints at two usage contexts (inspecting a real join vs. testing a hypothetical one), which is genuinely useful. But there is no explicit when-to-use guidance versus join_qa_sweep_tool (bulk) or recommend_fades_tool, and no exclusions or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.