generate_blog_post

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

With no annotations, the description must carry the behavioral burden, and it discloses only the output shape (headings, intro, conclusion, SEO optimization). It says nothing about generated length, tone/style controls, factual fidelity to the transcript, whether the call is slow or costly, or how failures manifest — meaningful gaps for a generation tool. Still, the stated output structure gives the agent real expectations beyond a bare verb.

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?

A single front-loaded sentence that packs the input, the transformation, and the output structure with zero filler. Nothing could be removed without losing information.

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?

The tool is simple (one required string, no annotations, no output schema), and the description covers what comes back structurally. However, for a generative transform with no annotations and no output schema, it should at minimum hint at output scale or that the result is newly authored content rather than an extraction.

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?

There is only one parameter and schema coverage is 100%, with the schema already describing it as 'The transcript text to convert into a blog post'. The description adds no constraint beyond that, so the baseline 3 for high schema coverage applies.

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 (convert), a specific input (a transcript), and a specific artifact (a full SEO-optimized blog post) with structural detail (headings, introduction, conclusion). It is distinguishable from the sibling generate_social_posts by output type, though it never explicitly contrasts itself with any sibling.

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?

Usage is only implied: the agent can infer it should be called when a transcript exists and a blog post is the desired output. There is no explicit when-to-use, when-not-to-use, or named alternative (e.g. summarize_text or generate_social_posts) for the same input.

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