Skip to main content
Glama

list_develop_parameters

Retrieve available photo editing parameters from Lightroom Classic to apply adjustments and automate editing workflows.

Instructions

List develop parameters known by this Lightroom Classic install.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The 'list_develop_parameters' tool handler, which calls 'develop.list_params' through the _call helper.
    async def list_develop_parameters() -> dict[str, Any]:
        """List develop parameters known by this Lightroom Classic install."""
        return await _call("develop.list_params")
Behavior2/5

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

With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, requires specific permissions, returns paginated results, or has rate limits. The description is minimal and lacks transparency beyond the basic purpose.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.

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?

Given the tool's simplicity (0 parameters, output schema exists), the description is minimally complete. However, with no annotations and an output schema, it could benefit from clarifying the return format (e.g., list of parameter names) or usage context to better guide the agent, leaving some gaps in overall context.

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?

There are 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add param semantics, but this is acceptable given the lack of inputs, warranting a baseline score of 4 for adequately handling the empty parameter set.

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

Purpose4/5

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

The description clearly states the verb ('List') and resource ('develop parameters'), specifying the scope ('known by this Lightroom Classic install'). It distinguishes from siblings like 'list_develop_groups' or 'list_develop_presets' by focusing on parameters, but could be more explicit about what 'develop parameters' entails (e.g., camera raw settings).

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 is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active photo), exclusions, or related tools like 'get_develop_settings' for specific values, leaving the agent to infer usage from context alone.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/4xiomdev/lightroom-classic-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server