generate_blog

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 states this is a generation tool that returns specific outputs, but doesn't mention important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or what happens if generation fails. The description is minimal and lacks operational context.

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 appropriately concise - a single sentence that communicates the core functionality and outputs. It's front-loaded with the main purpose. While efficient, it could potentially benefit from slightly more context given the lack of annotations and sibling tool differentiation.

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 generation tool with 4 parameters, no annotations, and no output schema, the description is minimally adequate. It covers what the tool does and what it returns, but doesn't address behavioral aspects, usage context, or error handling. The 100% schema coverage helps, but the description itself lacks completeness for a tool that presumably performs AI generation.

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 description doesn't add any parameter information beyond what's already in the schema. With 100% schema description coverage, all parameters are well-documented in the schema itself (including descriptions, enums, and defaults). The description mentions 'from a topic' which aligns with the required 'topic' parameter but provides no additional semantic context.

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 a complete AI-written blog post from a topic.' It specifies the verb ('generate'), resource ('blog post'), and output components (title, content, meta description, tags). However, it doesn't explicitly differentiate from siblings like 'generate_platform_content' or 'repurpose_content' beyond mentioning 'blog post' specifically.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'brainstorm_titles' (which might be used before this), 'publish_content' (which might be used after), or 'repurpose_content' (which might be an alternative for existing content). No context about prerequisites or exclusions is provided.

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