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framesail

by com.framesail

Get style

get_style
Read-onlyIdempotent

Fetch one style row — its inputs (reference material), analyzed fields (art_style, narrative_style, director_style, script_prompt, ...), and templates: {"character": url|null, "environment": url|null}, the two template images. A null there means that template is genuinely missing and needs generate_style_template; a URL means it exists (view_image it) — don't re-render it. Show fields to the user for review; fine-tune with update_style_fields. inputs_stale: true means the references changed since the last analysis run — the analyzed fields don't reflect them; offer the user analyze_style (it rewrites those fields).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
style_idYesStyle ID, as returned by create_style or list_styles

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description reveals important state semantics: null vs URL template meaning, the fact that inputs_stale indicates analyzed fields are outdated, and the downstream consequences of those states. This is meaningful behavioral context not present in the annotations.

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

Conciseness4/5

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

The description is dense and every clause earns its place, covering the return shape, null/URL handling, and stale-input behavior. It is slightly long but justified by the semantic complexity of the tool's return state.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of explaining return values and state interpretation. It covers the main fields, the templates object, null semantics, and inputs_stale behavior, giving an agent everything needed to correctly act on the response.

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?

There is only one parameter, style_id, and the schema already documents it fully as 'Style ID, as returned by create_style or list_styles.' The description adds no new parameter detail, but with 100% schema coverage, the baseline of 3 is appropriate.

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

Purpose5/5

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

The description opens with a specific verb and resource ('Fetch one style row') and enumerates exactly what that row contains: inputs, analyzed fields, and templates. It is clearly distinguishable from sibling tools like list_styles, analyze_style, update_style_fields, and generate_style_template.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives conditional routing guidance: null template values should lead to generate_style_template, URL values to view_image, stale inputs to analyze_style, and review/fine-tuning to update_style_fields. This explicitly tells an agent when to use this tool versus related alternatives.

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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TDQS

A3.6/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness4/5

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.

Resources