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elestirelbilinc-sketch

Media-infrastructure

by elestirelbilinc-sketch
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

upscale

Enhance image resolution using AI upscaling to improve clarity and detail for media projects.

Instructions

Upscale/enhance an image to higher resolution using AI. Cost: $0.15. Requires Tier 1+.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
media_urlYesURL of the image to upscale
scaleNoUpscale factor (2x or 4x)

Implementation Reference

  • sdk/vape_client/async_client.py:228-245 (handler)
    The implementation of the 'upscale' method in the asynchronous VAPE client, which sends a POST request to /v3/upscale.
    async def upscale(
    self,
    image_url: Optional[str] = None,
    image_base64: Optional[str] = None,
    scale: str = "2x",
) -> UpscaleResult:
    """Upscale an image using AI enhancement."""
    if not image_url and not image_base64:
        raise VAPEValidationError("Either image_url or image_base64 is required")

    payload = {"scale": scale}
    if image_url:
        payload["image_url"] = image_url
    if image_base64:
        payload["image_base64"] = image_base64

    data = await self._request("POST", "/v3/upscale", json=payload)
    return UpscaleResult.from_response(data)

Tool Definition Quality

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden and adds valuable behavioral context: it discloses the cost ('$0.15') and access requirement ('Requires Tier 1+'), which are not inferable from the schema. However, it lacks details on rate limits, output format, or error handling.

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, followed by cost and access details in two concise sentences. Every element earns its place without redundancy or fluff.

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?

Given the tool's moderate complexity (AI-based image processing), no annotations, and no output schema, the description is reasonably complete: it covers purpose, cost, and access. However, it omits details on output (e.g., format, size) and potential limitations (e.g., supported image types).

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%, so the schema fully documents both parameters. The description does not add meaning beyond the schema (e.g., it doesn't explain URL requirements or scale implications), meeting the baseline for high coverage.

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 specific action ('upscale/enhance an image to higher resolution using AI'), identifies the resource ('an image'), and distinguishes from siblings by focusing on resolution enhancement rather than editing, generation, or other media operations.

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 provides clear context for when to use this tool ('upscale/enhance an image'), but does not explicitly state when not to use it or name alternatives among siblings (e.g., 'ai_edit' for other enhancements). The cost and tier requirement offer practical constraints.

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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