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Get a style prompt

get_style
Read-only

Retrieve a style's STYLE.md to get its look, rules, and prompt; optionally include DEMO.md for how its demo film was made.

Instructions

Returns a style's STYLE.md: its look, rules and prompt. include_demo adds DEMO.md (how its demo film was made), which is long.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>"
    },
    "name": "get_style"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesStyle folder, e.g. "art-deco". Use find_styles to look one up.
include_demoNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already establish this as a safe, closed read (readOnlyHint=true, openWorldHint=false), so the description's job is to add what the annotations cannot. It does contribute real context: the return payload is a style's STYLE.md content and the DEMO.md is long, warning of a large response. It stops short of saying how the content is returned (single concatenated string vs. multiple fields) or whether slug must match a folder exactly.

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?

Two short sentences, front-loaded with what is returned and followed by the optional flag's effect and cost. No filler, no repetition of the title.

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?

For a simple two-parameter read tool with no output schema, the description covers the returned artifacts and the optional parameter's tradeoff. Only the response shape/format is left unstated, which is a minor gap at this complexity level.

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?

Schema coverage is only 50%, and the description fills the biggest gap by explaining exactly what include_demo toggles (adds DEMO.md about how the demo film was made) plus its size implication. Combined with the schema's slug hint and example, an agent can set both parameters correctly without guessing.

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?

Names a specific verb (returns) and a concrete resource (a style's STYLE.md), and spells out what that file contains: look, rules and prompt. It is clear what an agent gets, though it does not explicitly contrast itself with the sibling find_styles, which only appears in the parameter schema.

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

Usage Guidelines3/5

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

There is no explicit statement of when to call get_style versus find_styles or check_voice, so the selection logic is only implied via the slug parameter's 'Use find_styles to look one up' hint. The one real usage signal is conditional: include_demo is presented as an opt-in with a cost warning ('which is long'), which usefully tells an agent when not to request it.

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