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Valmera — AI Video Editor

by io.valmera
OverviewDiscussionsAdmin

Reframe for a vertical or square platform

auto_reframe

Measures subject location and retained visual detail across the kept footage, then sets the output frame. Automatic mode chooses a subject-focused crop or a fitted treatment according to the measured composition.

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": {
      "ratio": "<ratio>",
      "project_id": "<project_id>"
    },
    "name": "auto_reframe"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNo
ratioYes
followNo
project_idYesExplicit project identifier for this request. The connection's navigation pointer does not select the target.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / project_id / description
      Previous value: -"Required immutable scope for this call. Copy the id from list_projects/open_project/project_state; the active-project pointer is never used to guess."New value: +"Explicit project identifier for this request. The connection's navigation pointer does not select the target."
  2. Changed1 schema field changed
    • addedInput schema / properties / follow
      Added value: +{
+  "type": "boolean"
+}
  3. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already declare this is a non-destructive mutation (readOnlyHint false, destructiveHint false), so the description need not restate safety. It adds that the tool measures subject location and retained visual detail before setting the frame, and that automatic mode picks a treatment based on composition—useful behavioral context beyond the annotations, though it omits whether existing framing is overwritten or how long the analysis takes.

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?

The description is two sentences and front-loads the core action (measuring and setting the frame). It is appropriately sized, though the second sentence is somewhat dense and could clarify parameters instead of only describing automatic mode.

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?

For a mutation tool with four parameters and two enums, the description gives useful high-level behavior but leaves key details unspecified: how the ratio options affect output, what 'follow' controls, and when to choose a non-auto mode. With annotations covering safety and no output schema, it is adequate but incomplete for correct invocation.

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 only 25% (only project_id is documented), so the description must compensate. It hints at 'automatic mode' and the crop/pad choice, but does not explain the ratio enum values (9:16, 1:1, 4:5, 16:9, source), what 'follow' does, or how mode interacts with ratio. The gap is significant.

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

Purpose3/5

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

The description says it measures subject location and retained visual detail then sets the output frame, which indicates a reframing operation. However, it never explicitly states that it changes the aspect ratio to a vertical or square format, and it does not distinguish itself from siblings like set_frame or deliver_aspects. A clearer verb+resource statement is missing.

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 guidance on when to use this tool versus alternatives, nor when to choose among the mode options. The description mentions 'Automatic mode' but does not explain when to prefer auto, crop, pad, or pad_blur, leaving the agent to infer usage from the enum alone.

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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