Convert Tweet to Blog Post

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

Annotations already indicate readOnly (true), destructive (false), and idempotent (true). The description adds context on what the tool produces (BlogPost with fields) and the transformation process, enhancing understanding.

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?

Description is well-structured with sections for purpose, use cases, arguments, return values, and examples. Every sentence adds value, no redundancy.

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 3 parameters, no nested objects, and no output schema, the description covers the tool's functionality thoroughly, including return fields, formats, and use cases. It is complete for effective agent usage.

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 coverage is 100% with parameter descriptions. Description repeats and elaborates on parameters, adds examples, and explains the effect of 'include_engagement' and 'response_format', providing additional semantics beyond the schema.

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 'Convert a tweet into a formatted blog post', specifying the verb (convert) and distinct resource (tweet to blog post). It differentiates from siblings like get_tweet or extract_media by focusing on transformation and formatting.

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?

Description lists specific use cases (archiving, content creation, generating blog posts) and includes example prompts, but does not explicitly contrast with sibling tools or state when not to use.

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