generate_follow_up

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

No annotations are provided, so the description must disclose behavioral traits. It only states the tool generates an email, but fails to mention whether it sends it, the output format, or any side effects. This leaves significant ambiguity for the agent.

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 a single, front-loaded sentence with no wasted words. However, it lacks structure (e.g., separating purpose from behavior). It is concise but minimally adequate.

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 5 parameters, no output schema, and no annotations, the description is incomplete. It does not explain what the tool returns (e.g., email text, draft), nor does it clarify parameter details beyond the schema. The agent would need to infer or experiment.

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?

With only 20% schema coverage (only application_id has a description), the description does not add meaning to parameters like days_since_applied or candidate_name. It does not compensate for the low schema coverage, leaving parameter semantics unclear.

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 generates a follow-up email for an application without a response. It uses a specific verb ('generate') and resource ('follow-up email'), and distinguishes from sibling tools like auto_apply or generate_cover_letter, which have different purposes.

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 for applications lacking a response, but provides no explicit guidance on when to use versus alternatives, nor any 'when not to use' or prerequisite conditions. This is minimal guidance.

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