brand_audit_content

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

With no annotations, the description carries the full burden. It discloses the progressive nature of sessions and the return format (score with breakdown). However, it does not explicitly state whether the tool is read-only or if it modifies data, though the verb 'Check' implies a read operation. Overall, it adds useful behavioral context beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: it starts with the core purpose, then lists what it checks, gives usage guidance, explains progressive behavior, describes output, and ends with exclusions. Every sentence adds value with no repetition.

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

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

Despite no output schema, the description explains the return value (0-100 score with per-dimension breakdown and specific issues). It covers input format variances, progressive session behavior, and distinguishes from related tools. For a tool with only two parameters and no output schema, this is complete.

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

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

Schema coverage is 100%, but the description adds significant meaning: it explains that content can be raw text, HTML, or file paths, and how the format affects analysis (HTML gets visual + voice, plain text gets voice only). It also clarifies the depth parameter values ('quick', 'standard', 'deep') and their implications beyond the schema's enum list, fully compensating for any lack of detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check if content is on-brand — score any text or markup 0-100 for brand compliance.' It distinguishes from siblings by explicitly stating what it is not for (brand_audit for .brand/ validation, brand_preflight for HTML/CSS rule checking).

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

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

The description provides explicit when-to-use cues: 'Use when asked "is this on-brand?", "brand compliance score", "check brand alignment", or after generating any content.' It also states when not to use and names alternative tools, meeting the highest bar for usage guidance.

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