set_project_styleSet the project's default style — the style whose art/narrative/director fields drive its generations. Use after create_style to put a new visual identity into effect, or to switch a project between channel styles.
| Name | Required | Description | Default |
|---|---|---|---|
| style_id | Yes | ID of the style to make the project's default, from create_style or list_styles | |
| project_id | Yes | Project ID, as returned by create_project or list_projects |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains that the set style's fields drive generations, adding behavioral context beyond annotations. Annotations already indicate non-destructiveness and idempotency; the description adds that this affects generation output. A higher score would require explicitly mentioning idempotency or side effects like permission requirements.
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?
Two sentences, front-loaded with the main action, efficient and direct with no unnecessary words.
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?
For a simple two-parameter tool with no output schema and good annotations, the description is complete: it explains purpose, usage timing, and effect on generations. No gaps.
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 coverage is 100% with detailed parameter descriptions. The tool description adds no extra parameter meaning; it repeats that style comes from create_style/list_styles and project from create_project/list_projects, already in schema. Baseline 3 is appropriate.
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?
The description clearly states the tool sets a project's default style, specifying that this style's art/narrative/director fields drive generations. This distinguishes it from siblings like create_style (creates a style) and update_style_fields (updates style properties).
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?
Explicit usage guidance: 'Use after create_style to put a new visual identity into effect, or to switch a project between channel styles.' This tells when and why to use it, and implicitly contrasts with alternatives like create_style.
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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Several tool families overlap in purpose, such as await_jobs/get_workflow_status/get_pipeline_progress, update_segment_content/update_segment_prompts, director_note/project_director_note, and scan_script/rescan_voice_blocks. The descriptions do a good job distinguishing them, but an agent must read carefully to avoid misselection, and there are more than a couple of confusable pairs.
The set overwhelmingly follows a verb_noun snake_case convention with clear prefixes like get_, list_, set_, update_, create_, and delete_. Minor exceptions such as director_note, project_director_note, browse_audio_library, and whoami keep it from being perfectly consistent.
At 72 tools, this is far beyond the 50+ extreme range and creates a heavy navigation burden for an agent. Even though the pipeline is complex, this many tools is not well-scoped for an MCP surface.
The surface covers the full script-to-export pipeline: styles, assets, voices, storyboards, segments, scenes, and rendering all have substantial lifecycle support. Some gaps exist—no delete_channel, delete_segment, delete_voice_block, or delete_provider_key—but most missing operations can be worked around through existing tools.