Clipform

Upload Media Asset

clipform_upload_media_asset

Put one or more media files into your workspace media library (max 10, uploaded sequentially). This is step one of attaching media to a node - follow up with clipform_attach_node_media to place the returned media_asset_id on a node.

When a public URL is provided, the media is fetched and stored automatically. For video: ingested via Mux. For image: stored in Supabase. Word-level captions from clipform_generate_tts enable per-word highlighting in the viewer once attached - pass the caption_ref it returned instead of hand-copying the captions array.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`items`	Yes	One or more media items to create as workspace library assets
`context`	Yes	Describe the user's underlying goal in one sentence - not the tool you're calling.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`results`	Yes	One result per item, in order

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 7, 2026

addedInput schema / properties / items / items / properties / caption_ref

Added value: +{
+  "description": "caption_ref from clipform_generate_tts - an opaque handle that attaches that TTS run's word-level captions to this asset, resolved server-side. Preferred over captions.",
+  "type": "string"
+}

Changed4 schema fields changedSep 5, 2026

changedInput schema / properties / items / items / properties / captions / description

Previous value: -"Word-level captions from clipform_generate_tts. Required for per-word highlighting - pass the full objects including 'words' arrays."New value: +"Word-level captions from clipform_generate_tts. `words` is a required field on each caption (schema-enforced) - pass the full objects returned by clipform_generate_tts unmodified."

changedInput schema / properties / items / items / properties / captions / items / properties / words / description

Previous value: -"Per-word timestamps within the segment"New value: +"Per-word timestamps within the segment. Required - copy the full array from clipform_generate_tts verbatim."

addedInput schema / properties / items / items / properties / captions / items / properties / words / minItems
```
Added value: +1
```

changedInput schema / properties / items / items / properties / captions / items / required

Previous value: -[
-  "start",
-  "end",
-  "text"
-]New value: +[
+  "start",
+  "end",
+  "text",
+  "words"
+]

Changed3 schema fields changedAug 31, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "Describe the user's underlying goal in one sentence - not the tool you're calling.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "items"
-]New value: +[
+  "items",
+  "context"
+]

Changed1 schema field changedJul 17, 2026

addedInput schema / properties / items / items / properties / ai_generated

Added value: +{
+  "description": "Whether this media was AI-generated. Drives the viewer's disclosure chip - set true for AI-rendered/synthesized media.",
+  "type": "boolean"
+}

AddedJul 13, 2026

TDQS

A5/5.0

Behavior5/5

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

Annotations already indicate non-readonly, non-idempotent, non-destructive behavior. The description goes further by detailing how media is fetched and stored (video via Mux, image via Supabase), and how captions are attached (via caption_ref or provided captions). No hidden side effects or 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?

The description is well-structured and front-loaded: the first sentence states the core action and constraint. It efficiently packs usage notes and workflow context without redundancy, keeping every sentence meaningful.

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?

Given the tool's complexity (multiple media items, captions, integration with TTS), the description covers all necessary aspects: the workflow with sibling tools, handling of URLs, caption attachment options, and AI-generated/media-source settings. With an output schema present, no additional return-value explanation is needed.

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

Parameters5/5

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

Schema descriptions cover 100% of parameters and their nested fields. The tool description adds extra semantic meaning, such as the difference between 'caption_ref' (opaque handle) and 'captions' (full objects), and clarifies the 'context' parameter's purpose as describing the user's goal rather than the tool being called.

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?

The description clearly states the tool's function: 'Put one or more media files into your workspace media library' with explicit constraints (max 10, uploaded sequentially). It also distinguishes itself from sibling tools by referencing clipform_attach_node_media for the next step and describing its role in the media workflow.

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?

The description provides explicit usage guidance: it identifies this as 'step one' and directs the user to follow up with clipform_attach_node_media. It also explains when to use caption_ref vs captions, and how to obtain captions from clipform_generate_tts, giving clear 'when-to-use' instructions.

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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