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creative-tagger-mcp

creative-tagger-mcp

by stephenlavender
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_library_patterns

Analyze your creative library to uncover patterns in hooks, angles, and emotions. Get top values per dimension with percentages and diversification insights for portfolio analysis.

Instructions

Get pattern insights across the user's entire library: which hooks, angles, creative types, emotions they over- or under-index on. Returns top values per dimension with percentages plus rule-based diversification insights. Use this for portfolio analysis before recommending what to make next.

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": "get_library_patterns"
  }
}

Input Schema

NameRequiredDescriptionDefault
brand_nameNoExact workspace brand_name from list_workspaces

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It states the return structure (top values with percentages, diversification insights) but does not explicitly disclose side effects (e.g., read-only nature, permissions required, rate limits). Since it's a 'get' tool, read-only is implied but not stated, leaving some uncertainty.

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?

The description is two sentences, front-loading the action and output, then providing usage guidance. Every sentence is essential and no filler.

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?

For a single-parameter tool with no output schema, the description fully explains the return format (top values per dimension with percentages, diversification insights) and the usage context. No gaps remain.

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?

The single parameter 'brand_name' is described in the schema as 'Exact workspace brand_name from list_workspaces'. The description adds the qualifier 'Exact' and references 'list_workspaces' for source, which provides context beyond the schema's basic description. Schema coverage is 100%, so the description adds value.

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 clearly states the tool's purpose: 'Get pattern insights across the user's entire library' with specifics on what it analyzes (hooks, angles, creative types, emotions) and returns (top values with percentages, diversification insights). This distinguishes it from siblings like 'analyze_creative' or 'get_analysis'.

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

Usage Guidelines4/5

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

The description provides explicit usage context: 'Use this for portfolio analysis before recommending what to make next.' This tells the agent when to apply it. However, it does not mention when not to use it or offer alternatives, which would make it a 5.

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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