Find Alumni

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

With no annotations, the description carries the full burden. It discloses the critical behavioral trait that the server never reads LinkedIn and that the user must perform actions manually, which is beyond the schema. It does not mention error handling or side effects, but the key quirk is covered.

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 two sentences with no fluff. The purpose is front-loaded, and the behavioral note about LinkedIn is placed immediately after, making it highly readable and 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?

Given an output schema exists, the description need not detail return fields. It explains the two categories of results and the required workflow, making it complete for an agent to invoke correctly. No critical operational details are missing.

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 all four parameters are documented in the input schema. The tool description adds no parameter-specific details beyond what the schema already provides, so the baseline of 3 applies.

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 states a specific action ('Find people from the user's school to reach out to, at a target firm') and clearly differentiates from siblings like find_warm_paths by describing its dual output (existing contacts + LinkedIn search links). It also notes a key constraint ('This server never reads LinkedIn'), making its role unambiguous.

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 clearly states the tool's purpose and the workflow (user opens links, connects, re-imports), which implies when it's useful. However, it does not explicitly mention when to choose this over the sibling find_warm_paths, though the difference is inferable from the output description.

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