Suggest Targets

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

With no annotations, the description carries the transparency burden. It discloses key behavioral traits: candidates are un-targeted, each includes specific evidence fields, and the tool deliberately does not score fit. It goes beyond a generic 'suggests targets' by explaining its epistemic limits and what data it actually provides.

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 front-loaded with the core purpose and then explains the evidence fields and non-scoring stance. It is somewhat verbose in its rationale but every part adds useful behavioral or selection-relevant context, so it remains efficient.

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 description covers what the tool returns, why it returns it, what evidence is included, and what it deliberately does not do. With an output schema present and only two simple parameters, this is sufficient. It omits details like ordering or authentication, but those are not essential for correct invocation.

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 description coverage is 100%, so the baseline is 3. The description adds some context by clarifying that returned candidates are ones the user has not targeted yet, which relates to include_current, but it does not add significant meaning beyond the schema definitions for limit and include_current.

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 a specific action ('Returns candidates the user has not targeted yet') and a resource ('Firms worth considering'), and differentiates itself from siblings like list_targets by emphasizing candidates not yet targeted and evidence like job board readability and existing contacts.

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 gives clear context for use: it is for exploring new firms to target, providing evidence rather than a scored recommendation. It explicitly tells the agent not to rely on the tool for fit judgement. However, it does not name alternative tools or explicitly state when not to use it, leaving some routing to inference.

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