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Clipform

by io.github.Clipform

Search Media

clipform_search_media
Read-onlyIdempotent

Search images or stock video clips. Pass one query or many (max 10) - multiple queries run in one call instead of separate tool calls. Use results to feed into clipform_generate_video for narrated slideshow videos, or upload directly as still images via clipform_upload_media_asset then clipform_attach_node_media. All results are pre-cleared for commercial use. Results include a description (alt text where the provider has it) - use it to pick visually distinct images.

Example: { queries: [{ query: "saturn rings" }, { query: "mars surface", count: 3 }] } returns portrait images for both.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesDescribe the user's underlying goal in one sentence - not the tool you're calling.
queriesYesOne or more search queries to run

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchesYesResults grouped by query (items empty if a query found nothing or failed)

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds useful behavioral details beyond those: results are pre-cleared for commercial use, results include alt-text descriptions to aid image selection, and multiple queries are executed in one call. Orientation behavior ('portrait fills the 9:16 frame; landscape gets blur-pad framing') is also disclosed.

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 front-loaded with the core purpose, then gives workflow guidance, licensing context, result semantics, and a concrete example. Despite being a bit long, each sentence carries useful information and the example clarifies the array-shaped parameter.

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?

For a search tool with a rich schema, output schema, and strong annotations, the description covers invocation, result characteristics, downstream usage, and commercial-use caveat. Nothing essential is missing for an agent to call it correctly.

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

Parameters3/5

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

Schema coverage is 100% and every parameter already has a descriptive comment, so the baseline is 3. The description reinforces how queries work with an example and notes the max of 10, but it does not add substantial meaning beyond the schema.

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 opening line clearly identifies the action ('Search') and specific resources ('images or stock video clips'), which distinguishes it from sibling search tools like clipform_search_music and clipform_search_news. It also names the downstream tools that consume the results, reinforcing what this tool is for.

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

Usage Guidelines4/5

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

The description gives concrete usage context: pass one query or many, batch multiple queries in one call, and feed results into clipform_generate_video or into upload/attach steps. It does not explicitly say 'use X instead for music/news', but the media-type scope and workflow examples make the intended usage clear.

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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TDQS

A3.9/5.0
Disambiguation3/5

Most form/node CRUD tools are clearly distinct, but the render/generate trio (generate_video, render_video_template, render_composition) and get_responses vs get_results can be confused by name alone. The descriptions include strong disambiguation guidance, so the overlap is manageable but still present.

Naming Consistency4/5

The vast majority of tools follow a consistent clipform_verb_noun snake_case pattern, with create/get/update/delete/list used predictably. Minor deviations include get_more_tools lacking the clipform_ prefix and whoami not matching the verb_noun convention.

Tool Count2/5

At 34 tools, this is above the range where a toolset feels well-scoped, and several entries are auxiliary or internal (whoami, log_generation, get_more_tools, search_news). The domain is broad, but the surface could be consolidated without losing core capabilities.

Completeness4/5

The set covers form and node lifecycle, media upload/attachment, logic wiring, publishing, responses/results, and content generation (TTS, video, music, stock media). Minor gaps remain, such as no conditional branching in set_logic and no general media-library listing tool.

Resources