linkedin_metrics_by_ticker

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

No annotations provided. The description mentions pagination in the output example ('# paged') but does not clarify behavior like rate limits, authentication needs, or whether the tool is read-only. The focus on output format rather than behavioral traits 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 brief but poorly structured, embedding a JSON-like example that may confuse readers. It lacks clear sentences and mixes output format explanation with a representation, making it less concise and harder to parse.

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 complexity (nested object schema, multiple parameters, no output schema), the description is completely inadequate. It does not explain the tool's purpose in simple terms, parameter usage, or return behavior, leaving major gaps for an agent to use the tool correctly.

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%, and the description adds no information about any parameter. It mentions 'format' only in the output context but does not explain input parameters like 'ticker', 'date_from', 'date_to', or 'limit'. The agent cannot infer parameter semantics from the description.

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 'Normalized LinkedIn metrics' vaguely indicates the tool returns metrics for a ticker, but lacks a specific verb (e.g., 'retrieve' or 'get') and does not differentiate from sibling tools like 'screener_linkedin'.

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?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, context, or exclusions, leaving the agent to infer usage from the name and schema alone.

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