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Glama

run_curves

Apply a CurvesTransformation to a PixInsight view using custom control points for RGB, lightness, saturation, or individual color channels to adjust tones and colors.

Instructions

Apply a CurvesTransformation to a view. Provide control points as [[x,y], ...] for the desired channel: "RGB" (all), "L" (lightness), "S" (saturation), "R", "G", "B".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pointsYesControl points [[x,y], ...] from (0,0) to (1,1). Include endpoints.
channelYesChannel to apply the curve to
view_idYesView ID to process

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A3.5/5.0
Behavior2/5

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

The description only restates the operation; it does not disclose whether the view is modified in place or a new view is returned, whether the operation is reversible, or what response to expect. With no annotations supplied, the description carries the full burden of behavioral disclosure and does not meet it.

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?

Two short sentences with the core action first and the channel/coordinate clarification second. No filler, and each piece of information earns its place.

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?

The required inputs are fully covered by the schema and the description, so the agent can form a valid call. However, with no output schema and no annotations, the absence of any statement about return value or side effects leaves a modest but real gap.

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

Parameters4/5

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

The schema already documents all three parameters, and the description adds useful semantic detail by mapping channel names to meanings ('L' = lightness, 'S' = saturation) and clarifying the coordinate-list format. This goes beyond the bare schema but is not extensive.

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 action ('Apply a CurvesTransformation') and a clear target ('to a view'), and the subject matter is distinct from generic sibling process tools. It also enumerates channels, so the agent knows exactly what resource and mode the tool operates on.

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?

No guidance on when to choose this over siblings such as run_process, run_pixelmath, or run_lhe. The description does not describe preconditions (e.g., an open view) or conditions under which curves adjustment is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.