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List style references

list_style_references
Read-onlyIdempotent

List the signed-in user's style reference images (id, name, folder, project, updated_at, plus source_prompt and width/height when stored). Excludes trash. Metadata only — call get_style_reference to preview an image, then pass its id as style_reference_id to generate_pixel_art / generate_variants / apply_with_ai.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_style_references"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax rows (default 50).
project_idNoOnly return references scoped to this project.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description focuses on added context: results are user-scoped, trash is excluded, and no image payload is returned (metadata only), which is a meaningful disclosure an agent would otherwise have to discover. It stops short of describing ordering or pagination behavior beyond the limit parameter, so not a 5.

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 sentences, no filler. The resource scope and returned fields come first, followed by the exclusion and the hand-off workflow, so the most decision-relevant information is front-loaded.

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, the description usefully enumerates the returned fields (id, name, folder, project, updated_at, source_prompt, width/height) so the agent knows what shape to expect. Minor gaps remain around result ordering and how limit interacts with large collections, but nothing essential to calling it correctly is missing.

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?

Schema coverage is 100% and both parameters (limit, project_id) are fully documented in the schema, so the description is not obligated to restate them. It adds only indirect context by naming "project" among returned fields, without explaining how project_id filters versus what the project field contains — baseline 3.

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?

States a specific verb and resource ("List the signed-in user's style reference images"), names the exact fields returned, and scopes the result set ("Excludes trash"). This is clearly distinguishable from get_style_reference, which is explicitly framed as the single-item preview counterpart.

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?

Explicitly routes the agent: this tool is metadata only, use get_style_reference to preview an image, then feed the resulting id as style_reference_id into generate_pixel_art / generate_variants / apply_with_ai. That is a concrete when-to-use-this vs when-to-use-a-sibling chain rather than implied guidance.

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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