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bbernstein

LacyLights MCP Server

by bbernstein

get_project

Retrieve high-level metadata and resource counts for a LacyLights theatrical lighting project to assess scope before exploring fixtures, looks, or cue lists.

Instructions

Get high-level project information including metadata and counts.

Returns:

  • Project metadata (id, name, description, timestamps)

  • Resource counts (fixtureCount, lookCount, cueListCount)

Does NOT include:

  • Fixture details (use list_fixtures or get_fixture_inventory)

  • Look details (use list_looks)

  • Cue list details (use list_cue_lists or get_cue_list_details)

Use this tool first to understand project scope before drilling down into specific resources.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.7.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the return shape (metadata fields plus fixtureCount/lookCount/cueListCount) and scopes out what is not returned, which is useful. However, it says nothing about permissions required, behavior on a nonexistent or inaccessible projectId, or whether counts are cheap or expensive to compute.

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?

Front-loaded with the core purpose, then cleanly sectioned into what is returned versus what is not, with each exclusion routed to a named alternative. No sentence is filler and the routing value justifies the bulleted length.

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?

With no output schema and no annotations, the description correctly compensates by enumerating the returned fields and the resource counts. The main residual gap is failure behavior for an invalid or inaccessible projectId, which an agent would need to know.

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?

Only one parameter exists and schema description coverage is 100% ('Project ID to retrieve'), so the schema already defines it fully. The description mentions 'id' in the returned metadata but adds no input semantics such as accepted ID formats or source. Baseline 3 is appropriate.

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?

States a specific verb and resource ('Get high-level project information including metadata and counts') and enumerates exactly what is returned. It differentiates from list_fixtures, list_looks, and list_cue_lists, but fails to distinguish itself from the sibling 'get_project_details', which is the most confusable tool in the set.

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?

Explicitly prescribes a workflow ('Use this tool first to understand project scope before drilling down') and names concrete alternatives for each excluded resource type (list_fixtures, list_looks, list_cue_lists, get_cue_list_details). It gives no guidance on when to choose get_project over get_project_details, which leaves the key selection decision unresolved.

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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