li_get_demographics_report

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

No annotations exist, so the description carries the full burden. It explains that the tool returns impressions, clicks, spend, leads, and conversions per dimension value, but does not disclose behavioral traits like required permissions, data freshness, pagination, or handling of multiple campaigns.

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 concise (6 sentences) and well-structured, front-loading the purpose, listing options with context, stating return metrics, and ending with use cases. No superfluous sentences.

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 tool has 6 parameters (5 undocumented in both schema and description), no output schema, and moderate complexity, the description omits critical context for filtering (campaign_ids, ad_account_id, date range) and does not explain the response structure beyond listing metrics.

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?

The description adds significant value for the pivot parameter by explaining each enum value and grouping them by use case, supplementing the schema's 17% coverage. However, it provides no semantics for other parameters like campaign_ids, ad_account_id, start_date, end_date, and fields.

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: breaking down LinkedIn campaign performance by a demographic dimension. It lists all pivot options and distinguishes itself from siblings like li_get_campaign_performance by focusing on demographic breakdowns and specific use cases (buyer-persona fit, ABM).

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 clear usage contexts for each pivot option (e.g., persona fit, ABM analysis, geo reporting) and implies when to use the tool but does not explicitly state when not to use it or mention alternatives like li_get_campaign_performance for overall metrics.

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