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

The description adds meaningful behavioral detail beyond the annotations: structured fields are FREE, brand_doc costs 5 credits, topics are appended with a 12-per-call cap, keywords are auto-proposed when omitted, and nothing is published. These are non-obvious side effects and constraints that an agent needs to know before invoking the tool.

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 dense but every sentence carries useful information, from billing to workflow to side effects. It is appropriately sized for an 11-parameter tool, though the long prose paragraph could be better structured with bullets or explicit sequencing. It is front-loaded with purpose and cost, which helps an agent scan it quickly.

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?

For a tool of this complexity, the description covers the workflow, required inputs, billing, topic behavior, and the fact that nothing is published. With no output schema, a brief note about what the call returns or how to verify success would strengthen it, but the provided description is already sufficient for an agent to invoke it correctly in most cases.

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?

Even though schema description coverage is 100%, the description adds crucial semantic guidance: first-time setup requires at least voice and platforms, space_id/new_space are mutually exclusive routes, topics are appended, and brand_doc should only be passed when the user provides a written template. This materially improves parameter understanding beyond the raw schema.

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 opens with a specific action: 'Turn the content engine on for a brand from an onboarding conversation, or update its settings later.' This clearly identifies the resource (a brand's content space) and the operation (set up or update), and it does not merely restate the tool name. The title and description together distinguish it from sibling tools like generate_posts or manage_content_topics.

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 gives a concrete workflow: collect answers first via the setup prompt, read them back for confirmation, then call once. It also specifies when to use space_id vs new_space and when to pass brand_doc. However, it does not explicitly name alternatives or state when not to use this tool versus a sibling, so it stops short of a 5.

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