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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the analysis categories but does not describe the output format, any side effects, or limitations. Since this is a non-destructive analysis tool, the omission is less critical, but the description still lacks explicit details about what the tool returns or how it behaves beyond the listed evaluation areas.

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 front-loaded, opening with a clear one-sentence purpose, followed by a focused bullet list of analysis areas. Every sentence earns its place, with no redundant or filler content.

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 an analysis tool with 3 parameters, one enum, and an output schema present, the description covers the core functionality and supported platforms. It does not detail the return format, but the existence of an output schema likely handles that. The description is complete enough for an agent to understand what the tool does and when to invoke it, though it could optionally mention any preconditions beyond the schema's min length.

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?

The input schema provides 100% description coverage for all parameters, so the baseline is 3. The description adds no extra meaning about the parameters themselves; it only lists the analysis dimensions (e.g., character limits, algorithm signals) which indirectly relate to the 'platform' parameter but do not deepen understanding of 'content' or 'target_audience' beyond what the schema already states.

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 states a specific verb ('Analyze') and resource ('content for platform-specific optimization'), and clearly distinguishes itself from generic analysis tools like analyze_content by focusing on platform constraints and algorithm preferences. The bullet points further specify the exact evaluation areas, making the tool's purpose unmistakable.

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 implies usage for platform-specific optimization but does not explicitly state when to use this tool versus siblings like analyze_content or analyze_persuasion. No exclusions or alternative conditions are mentioned; the guidance is inferred from the purpose rather than directly stated.

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