generate_outreach

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

With no annotations, the description carries full burden. It discloses that three variants are created, references candidate's repos/contributions/tech stack, and warns about placeholders if company_name/sender_name are not provided. This covers key behavioral traits.

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 well-structured with sections and front-loads the purpose. The all-caps warning is prominent. It could be slightly more concise, but it remains readable and informative.

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 has an output schema, the description doesn't need to detail return values. It covers purpose, usage, parameters, and behavioral notes comprehensively for a 5-parameter tool without annotations.

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 0%, so description must compensate. It provides clear explanations for all five parameters, including defaults and the behavior if omitted (e.g., placeholders for company_name and sender_name). The tone parameter specifies allowed values.

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 it generates personalized recruiter outreach messages for a GitHub candidate, creating three message variants. This is distinct from sibling tools like bulk_score or search_developers, which serve different functions.

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 explicitly instructs to ask the user for company_name and sender_name before calling the tool, providing clear usage context. It does not, however, specify when not to use the tool or mention alternatives, but the purpose is specific enough.

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