Analyze an act's script to generate lighting cue suggestions and build a cue list for the project.
Generate cue suggestions for an entire act based on script analysis
| Name | Required | Description | Default |
|---|---|---|---|
| actNumber | Yes | Act number to generate cues for | |
| projectId | Yes | Project ID to work with | |
| scriptText | Yes | Script text for the act | |
| cueListName | No | Optional name for the cue list | |
| existingLooks | No | Optional existing look IDs to reference |
Changes observed during successful MCP inspections.
v1.7.0Input schema / properties / existingLooksAdded value: +{
+ "description": "Optional existing look IDs to reference",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+}Input schema / properties / existingScenesRemoved value: -{
- "description": "Optional existing scene IDs to reference",
- "items": {
- "type": "string"
- },
- "type": "array"
-}v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. 'Suggestions' hints at a non-mutating operation, but it never confirms whether cues are persisted, whether the caller must then call bulk_create_cues, or what permissions are needed. For a tool whose siblings include bulk_create_cues and create_cue_sequence, this ambiguity is material.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no wasted words. It is efficient, though arguably too terse given the absence of annotations and output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A five-parameter tool with no annotations and no output schema needs more than one sentence. The description omits whether output is persisted, how the optional cueListName and existingLooks parameters alter behavior, and how the result relates to bulk_create_cues.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all five parameters, including the optional cueListName and existingLooks. The description adds no format, constraint, or relationship detail beyond restating that the act's script text drives generation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (generate) and resource (cue suggestions) with a clear scope (an entire act) and input basis (script analysis). It is distinguishable from analyze_script and bulk_create_cues because it produces 'suggestions' rather than analysis or committed cues, though it never names those siblings explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this versus analyze_script, analyze_cue_structure, or bulk_create_cues, and no prerequisites or exclusions. The agent must infer the workflow position from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.