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brand_audit_content

Evaluate content brand compliance with a 0-100 score analyzing color, font, voice, anti-patterns, and message coverage.

Instructions

Check if content is on-brand — score any text or markup 0-100 for brand compliance. Checks color/font usage, voice alignment, anti-pattern violations, and message coverage. Use when asked 'is this on-brand?', 'brand compliance score', 'check brand alignment', or after generating any content. Works progressively: Session 1 scores tokens, Session 2 adds visual compliance, Session 3 adds voice and messaging. Returns 0-100 score with per-dimension breakdown and specific issues. NOT for .brand/ directory validation (use brand_audit) or HTML/CSS rule checking (use brand_preflight).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesContent to audit: raw text, an HTML string, or a file path ending in .html/.htm/.md/.txt. HTML gets visual + voice analysis; plain text gets voice analysis only.
depthNoAudit depth: 'quick' = token compliance only, 'standard' = + voice and message coverage, 'deep' = + visual anti-patterns. Default: 'standard'.standard
Behavior3/5

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

No annotations are provided, so the description must convey behavioral traits. It explains the progressive session behavior and return format, but does not disclose side effects, authentication needs, or whether data is stored or modified.

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 informative but somewhat lengthy. It front-loads the purpose and key details, with each sentence contributing useful information. Slightly longer than necessary but still efficient.

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?

Given the tool's complexity, two parameters, and many sibling tools, the description covers purpose, usage, behavior, and exclusions well. It could mention output structure more explicitly but is adequate.

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 description coverage is 100% with clear parameter descriptions. The description adds value by explaining how content type affects analysis (HTML vs plain text) and defining depth levels beyond the enum labels.

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 audits content for brand compliance with a score 0-100, and specifies it checks color/font, voice, anti-patterns, and message coverage. It also directly distinguishes from siblings like brand_audit and brand_preflight.

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?

Explicit usage triggers are provided (e.g., 'is this on-brand?', 'brand compliance score'), and alternatives are given for cases not handled (e.g., use brand_audit for .brand/ directory validation, brand_preflight for HTML/CSS rules).

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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