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

Annotations are empty, so the description carries the behavioral burden. It does disclose a key trait: 'Deterministic template engine (MVP)', which signals predictable, template-limited output. However, it does not describe output format, handling of the optional audience field, or limitations of the MVP beyond the label.

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?

Two short sentences with no filler. The core action and inputs are front-loaded, and the 'Deterministic template engine (MVP)' caveat adds useful context without bloat.

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 low-complexity generation tool with three simple parameters and no nested objects, the description is largely sufficient: inputs are clear and the output is inferable as a LinkedIn post draft. The main gap is not describing the output format or how the optional audience parameter affects generation, but the schema covers the parameter itself.

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 description coverage is 100%, so the structured schema already documents all three parameters. The description adds only the connection between brand_voice, brief, and the generated post, which is useful but does not meaningfully extend the schema's own parameter descriptions.

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 names a specific verb ('Generate'), a concrete resource ('Polish LinkedIn post'), and the inputs it acts on ('brand_voice + brief'). It is clearly distinct from sibling tools like anti_slop_edit and week_content_plan, though it does not explicitly call out those alternatives.

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?

There is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The 'MVP' note implies a limited, template-based use case, but the description leaves the selection criteria entirely to the agent's inference.

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