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stephenlavender

creative-tagger-mcp

generate_naming

Generate naming convention strings from creative attributes to produce API-compatible standard, full, compact, and reporting names.

Instructions

Generate V1-compatible standard, full, compact, and reporting naming convention strings from creative attributes. Use when you already have classified attributes (for example from analyze_creative) and need the same naming structure the API returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctaNo
talentNo
emotionNo
versionNo
audienceNo
cta_typeNo
durationNo
hook_typeNo
asset_typeNoUGC
audio_typeNo
brand_nameYes
offer_typeNo
seasonalityNo
talent_typeNoNo Talent
aspect_ratioNo9:16
visual_styleNoNative
visual_formatNoTalking Head
voiceover_toneNo
messaging_angleNo
Behavior2/5

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

With no annotations, the description fails to disclose behavioral traits such as side effects, authentication needs, or return format details. It only describes the generation action but doesn't address whether it modifies state or requires specific permissions.

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 long, each serving a distinct purpose: the first defines the action, the second provides usage context. No extraneous information, front-loaded with key details.

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

Completeness2/5

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

Given the tool has 19 parameters, no output schema, and no annotations, the description is insufficient. It doesn't specify output format, required parameter dependencies, or how the 19 attributes map to return strings. The reliance on external classification is noted but not enough to make the tool fully self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not elaborate on individual parameters beyond mentioning 'creative attributes.' It adds no meaning to specific fields like brand_name, cta, or talent, leaving the agent to infer their semantics from names alone.

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 generates V1-compatible naming convention strings (standard, full, compact, reporting) from creative attributes. It also distinguishes itself from siblings by referencing analyze_creative as a prerequisite, making its purpose unambiguous.

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 explicitly advises using this tool after having classified attributes, citing analyze_creative as an example. While it doesn't list when not to use it or alternatives, the context provides clear guidance on the appropriate scenario.

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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