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Set auto-frame for a platform

update_frame_settings

[writes flayr data · write scope] Frame every image posted to a platform automatically (frameRef), or stop (frameRef null). Applies to posts published or scheduled from now on. Confirm with the user first. (Wraps POST /api/v2/frames/settings.)

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": {
      "platform": "<platform>",
      "frameRef": "<frameRef>"
    },
    "name": "update_frame_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault
aspectNo
frameRefYes
platformYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the bar is lower; the description still adds the required `write` scope, that it mutates flayr data, the non-retroactive effective window, and that it wraps POST /api/v2/frames/settings. It does not discuss reversibility or what happens to already-scheduled posts beyond the 'from now on' statement.

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 scope/annotation tag is front-loaded, the core behavior follows immediately, and no sentence is redundant. The trailing endpoint wrapper is boilerplate but short and useful for debugging, so nothing is wasted.

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 no output schema, the description covers the write scope, the forward-only effect, and the confirmation requirement, which is most of what an agent needs. The gap is the undocumented `platform` and `aspect` parameters, which leave the agent unable to choose valid values for two of the three inputs.

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 0% and there is no output schema, so the description carries the full burden for three parameters. It only clarifies frameRef (a frame reference, or null to stop); `platform` (which platform identifiers are valid) and `aspect` (an enum of 1:1, 4:5, 9:16, 16:9, and how it interacts with the chosen frame) are entirely unexplained.

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 ('frame every image posted to a platform automatically') and explicitly covers both directions of the toggle, including the null case that disables it ('or stop (frameRef null)'). An agent can distinguish this from get_frame_settings (read) and apply_frame (per-item) without opening any 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?

Gives a real usage constraint — the setting only affects posts published or scheduled from now on — plus an explicit prerequisite, 'Confirm with the user first.' It does not, however, name an alternative tool or say when to prefer apply_frame over this platform-level default, so the when-not guidance is partial.

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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