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OpenClip

by app.openclip
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List Caption Presets Tool

list_caption_presets
Read-only

List the caption style presets available for rendering. Each preset has a key (pass it as caption_preset to render_clip), a display name, a short description, and a category. Call this to discover valid caption_preset values before rendering — render_clip rejects any key not in this list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
caption_presetsYesEvery caption preset render_clip accepts. Any key not listed here is rejected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "caption_presets": {
+      "description": "Every caption preset render_clip accepts. Any key not listed here is rejected.",
+      "items": {
+        "properties": {
+          "category": {
+            "description": "Grouping for the preset, e.g. professional.",
+            "type": "string"
+          },
+          "description": {
+            "description": "What the preset looks like.",
+            "type": "string"
+          },
+          "key": {
+            "description": "Pass this as `caption_preset` to render_clip.",
+            "type": "string"
+          },
+          "name": {
+            "description": "Display name of the preset.",
+            "type": "string"
+          }
+        },
+        "required": [
+          "key",
+          "name",
+          "description",
+          "category"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "caption_presets"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds valuable context beyond that: it specifies the structure of each preset (key, name, description, category) and the validation behavior of render_clip, which helps the agent understand the tool's role in the workflow. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

Two sentences with zero waste: the first establishes purpose and output fields, the second explains when to use it and the consequence of not doing so. Front-loaded with purpose, and every sentence earns its place.

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

Completeness5/5

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

Complete for a zero-parameter, read-only list tool with an output schema. The agent knows exactly what to expect (fields and categories), when to call it, and why it matters (render_clip validation). Nothing an agent needs to correctly invoke it is missing.

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 and an empty input schema, so there is nothing to explain about parameters. The description appropriately focuses on the output structure instead, which is beyond what the schema provides. Baseline for 0 params is 4, and the description meets that adequately.

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

Purpose5/5

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

States a specific verb and resource ('List caption style presets') with a clear scope (available for rendering) and distinguishes it from sibling list tools (list_videos, list_agents, etc.) by focusing on caption presets. It also mentions the output fields (key, name, description, category), making the purpose unambiguous.

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

Usage Guidelines5/5

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

Explicitly instructs to call this to discover valid caption_preset values before rendering, and warns that render_clip rejects any key not in this list. This provides clear when-to-use guidance and names the dependent tool (render_clip), leaving no ambiguity about when to invoke it.

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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