get_similar_profiles

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

No annotations are provided, so the description carries the full burden. It mentions the API source and factors used for similarity, but lacks critical behavioral details: it doesn't specify if this is a read-only operation, what permissions are required, whether there are rate limits, how relevance scoring works, or the format of returned profiles. For a tool with no annotations, this leaves significant gaps.

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 and appropriately sized. It starts with a clear purpose statement, adds context about the API and factors, then lists parameters and returns in separate sections. Every sentence adds value, with no wasted words, though it could be slightly more front-loaded by integrating the API mention earlier.

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 2 parameters with 0% schema coverage and no annotations, the description does a decent job explaining parameters and mentioning the return format. However, with an output schema present, it doesn't need to detail return values, but it still lacks behavioral context for a tool with no annotations. It's minimally adequate but has clear gaps in transparency.

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 0%, so the description must compensate. It effectively explains both parameters: 'profile_id' as a 'LinkedIn public ID' with an example, and 'limit' as the 'maximum number of similar profiles to return' with a default. This adds meaningful context beyond the bare schema, though it doesn't detail constraints like ID format or limit ranges.

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's purpose: 'Get profiles similar to a given profile' and mentions it uses 'Professional Network Data API' with specific factors like 'industry, role, skills, and other factors'. It distinguishes itself from siblings like 'get_profile' or 'search_people' by focusing on similarity rather than direct retrieval or search. However, it doesn't explicitly contrast with all similar siblings like 'batch_get_profiles'.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is preferred over 'search_people' or 'batch_get_profiles', nor does it specify prerequisites or exclusions. The context is implied but not explicit.

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