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Podcast MCP

by calebn
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Python
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export_audio_tool

Encode mastered audio into export formats from pipeline.yaml or formats objects, replacing export/ only after every file is written. Cancel stops encoding and preserves the prior export.

Instructions

Encode mastered audio to export/ using pipeline.yaml formats, or formats objects.

All or nothing: files replace export/ only after every one is written. When the client cancels the request (notifications/cancelled) the encode stops, the tool raises CancelledProgress("Export cancelled") and an earlier export is left untouched. Do not wait for a reply to the cancelled request (over JSON-RPC there is none); check export/.

Input Schema

NameRequiredDescriptionDefault
formatsNo
project_pathNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.1.1
    • addedInput schema / properties / formats
      Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "additionalProperties": true,
+        "type": "object"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Formats"
+}
    • removedInput schema / properties / formats_json
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "title": "Formats Json"
-}
    • addedInput schema / properties / project_path / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / project_path / default
      Added value: +null
    • removedInput schema / properties / project_path / type
      Removed value: -"string"
    • removedInput schema / required
      Removed value: -[
-  "project_path"
-]
  2. First observedv0.1.0

TDQS

B3.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses all-or-nothing atomicity ('files replace export/ only after every one is written') and precise cancellation semantics (encode stops, CancelledProgress raised, prior export untouched, no JSON-RPC reply). It omits permission/auth requirements, but the key behavioral traits are unusually well covered.

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?

Purpose is front-loaded in the first sentence, and the second paragraph is dedicated to the non-obvious cancellation contract. The cancellation detail is somewhat dense but every clause earns its place by preventing a real misuse (waiting for a reply that never comes).

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?

An output schema exists, so return values need not be explained, and cancellation behavior is thoroughly documented. The definition is still incomplete for invocation because one of two parameters is entirely undocumented and no format-object structure is provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and neither parameter is documented structurally. The description hints that 'formats' come from pipeline.yaml or formats objects, adding marginal meaning, but 'project_path' is never mentioned and no format object shape is given, leaving a significant gap.

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?

The description gives a specific verb and resource ('Encode mastered audio to export/') plus the format source (pipeline.yaml or formats objects), which distinguishes it from export_transcript and export_social_clips_tool. However, it does not explicitly name or contrast those siblings, so differentiation is left to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance and no mention of alternatives such as render_final, bounce_audio_tool, or render_preview. The only implied usage is that formats come from pipeline.yaml, which is a format detail rather than routing guidance.

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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