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Klipa

by ai.klipa.mcp
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Export AI clips

export_clips

Produces the video files of clips found by create_ai_clips and returns a download link and a preview for each (valid 72 hours).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>",
      "clip_numbers": "<clip_numbers>"
    },
    "name": "export_clips"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatNoAspect ratio; empty = the one chosen for the analysis
job_idYesjob_id of the finished create_ai_clips analysis
clip_numbersYesClip numbers to export (the clip_index values from the analysis)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, idempotentHint=false, destructiveHint=false), the description discloses the return shape (a download link and a preview per clip) and a concrete behavioral constraint: links are valid for 72 hours. It omits credit cost and what happens on repeat exports or invalid clip numbers, so it is not fully transparent.

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?

A single front-loaded sentence with zero waste: it states what is produced, what is returned, and the freshness constraint, in that order.

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

Completeness4/5

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

With no output schema, the description usefully covers the return values and their 72-hour expiry, and it identifies the required upstream job. It leaves minor gaps around failure modes (invalid clip numbers, the 10-item cap, credit usage) for a non-idempotent export operation.

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 description coverage is 100%, including the enum and its empty-string default for 'format' and the meaning of clip_numbers as clip_index values, so the schema already does the work. The description adds no parameter-level detail 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?

States a specific verb and resource ('Produces the video files of clips') and ties it to the upstream producer create_ai_clips, so an agent can distinguish it from create_ai_clips and the other editing siblings without inspecting the schema.

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 makes the prerequisite explicit by naming create_ai_clips as the source of the clips, and the schema clarifies that the job must be a finished analysis. It does not name an alternative or state when not to use it, so it falls short of a 5.

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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