prospect_research_find_prospects

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

With no annotations, the description discloses caching (30-day) and source (Fiber.ai linkedin search). It honestly portrays a read-only search. It could mention rate limits or usage restrictions to be more transparent, but the existing info is sufficient.

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?

Two concise sentences that front-load the core action and source. No redundant phrases; every part provides essential 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?

Covers identification methods (company name, domain, linkedin slug), optional filters, and output details. No output schema exists, so the description compensates well. Could mention if more than 10 results are possible or pagination, but not essential for a simple search tool.

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 value by specifying the output fields (name, title, LinkedIn URL, skills) beyond the schema, helping agents understand what the tool returns.

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 'discovers people at a company using Fiber.ai LinkedIn search'. It specifies the verb ('discovers'), resource ('people at a company'), and method, differentiating it from sibling tools like 'search_linkedin_people' by naming the source and exact output fields.

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 finding multiple people at a specific company, which contrasts with sibling tools (e.g., search_linkedin_people for general search, prospect_research_research_prospect for individual research). However, it lacks explicit when-to-use/not-use guidance or alternative suggestions.

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