generate_platform_content

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'creates platform-optimized content with correct character limits,' which adds some context about output formatting. However, it lacks details on permissions, rate limits, error handling, or what the generated content looks like (e.g., format, structure), which is a significant gap for a content generation tool with zero annotation coverage.

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 front-loaded and efficient with two sentences that directly convey the tool's function and key features. Every sentence earns its place: the first states the purpose, and the second adds behavioral context without redundancy. It's appropriately sized for the tool's complexity.

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?

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the basic purpose and hints at output behavior, but without annotations or output schema, it lacks details on permissions, errors, or return format. This makes it adequate but not fully comprehensive for safe and effective use.

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 schema already documents all parameters (topic, platforms, tone, language) with descriptions and enums. The description adds minimal value beyond the schema by implying topic-based generation and platform optimization, but it doesn't provide additional syntax, examples, or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Generate social media posts directly from a topic (no blog needed).' It specifies the verb ('generate'), resource ('social media posts'), and scope ('from a topic'), distinguishing it from sibling tools like generate_blog. However, it doesn't explicitly differentiate from repurpose_content or publish_content, which keeps it from a perfect score.

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 by stating 'no blog needed,' which suggests this tool is for direct social media content creation rather than blog-based generation. It doesn't provide explicit when-to-use vs. when-not-to-use guidance or name alternatives like repurpose_content for existing content adaptation, leaving usage context somewhat implied rather than fully articulated.

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