li_get_conversion_events

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

No annotations provided, so description carries full burden. It does not disclose read-only nature, authentication requirements, rate limits, or pagination behavior. The description is straightforward but lacks explicit behavioral warnings or details beyond the function.

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?

Description is three sentences with no wasted words: first sentence states purpose, second enumerates return fields, third lists use cases. Well front-loaded 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 no output schema, description adequately explains return values (name, type, enabled status, attributionType, attribution windows, Insight Tag). It covers typical use cases but could mention pagination implications (page_size parameter) and prerequisites (ad account access). Minor gaps.

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 coverage is 67% (ad_account_id and enabled_only have descriptions). The description does not add significant parameter-level details beyond the schema; it lists return fields rather than elaborating on parameters like page_size. Baseline score of 3 is appropriate.

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?

Description clearly states it lists LinkedIn conversion event definitions on an ad account, and enumerates return fields. This distinguishes it from sibling tools like li_get_conversion_performance which return performance data, not definitions.

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?

Description explicitly states use cases: audit conversion event setup, confirm event names before pulling conversion performance, verify attribution window configuration. It does not explicitly exclude other uses or mention alternatives, but provides clear context for when to use.

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