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Glama

get_state

Retrieve the current image and recipe state so AI agents can inspect active film simulation settings before adjusting exposure, filtration, or cropping.

Instructions

Current image and recipe.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden and discloses almost nothing: it does not confirm the call is read-only and side-effect free, whether it fails when no image is loaded, or how the state is represented. Only the 'get_' naming convention implies a safe read.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four words with zero waste, but the brevity crosses into under-specification: it is a noun fragment rather than a statement, so there is nothing to front-load and no structure to speak of.

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 zero-parameter read of editor state with no output schema and no annotations, the description should at least say it returns the currently open image and its applied recipe/settings, and what happens when no image is open. It gestures at the return contents but leaves the critical edge case and format unexplained.

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 tool takes zero parameters, so there is nothing for the description to disambiguate or document; the baseline for a parameterless tool applies.

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 fragment 'Current image and recipe' names the two pieces of data returned, which does add content beyond the tool name 'get_state', but it contains no verb and never states that it retrieves/returns anything. It is distinguishable from siblings like open_image or develop only by inference from the noun phrase.

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 call this versus open_image, loupe, or compare, nor any precondition (e.g., must an image already be open). Usage is left entirely to the agent's inference from the name.

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